{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"In this era, data has become very important, as it is considered the oil of the 21 century. Data surrounds us from everywhere and all institutions and countries are producing a huge amount of data daily. One of the most exciting fields these days is the field of data science. To be a data scientist,you must have knowledge of statistical concepts and probability, so this notebook will take you on a fun journey to understand probability distributions and how to apply them in real data.\nIn this notebook we will explain pribability distributions and apply it in real dataset.","metadata":{"execution":{"iopub.execute_input":"2022-06-28T16:11:01.984901Z","iopub.status.busy":"2022-06-28T16:11:01.98445Z","iopub.status.idle":"2022-06-28T16:11:01.990392Z","shell.execute_reply":"2022-06-28T16:11:01.989356Z","shell.execute_reply.started":"2022-06-28T16:11:01.984858Z"}}},{"cell_type":"code","source":"import pandas as pd \nimport numpy as np \nimport seaborn as sns \nfrom scipy import stats \nimport matplotlib.pyplot as plt\n#from empiricaldist import Pmf , Cdf\nfrom matplotlib.ticker import PercentFormatter","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"We will explain the probability distributions on Boston House , Titanic , athlete_events and police project data.\nSo, we need to import this data","metadata":{}},{"cell_type":"code","source":"df_titanic = pd.read_csv('../input/titanic/train.csv')\ndf_house = pd.read_csv('../input/house-prices-advanced-regression-techniques/train.csv')\ndf_police = pd.read_csv('../input/stanford-open-policing-project/police_project.csv')\ndf_olympic = pd.read_csv('../input/120-years-of-olympic-history-athletes-and-results/athlete_events.csv')","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def label_graph(ticksfont , x_label , y_label , title_label , fontsize):\n    \n    plt.xticks(fontsize = ticksfont)\n    plt.yticks(fontsize = ticksfont)\n\n    plt.xlabel(x_label, fontsize = fontsize)\n    plt.ylabel(y_label , fontsize = fontsize)\n    plt.title(title_label, fontsize = fontsize)","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Probability distributions can be classified into two categories\n\n##### 1- Disceret distributions \n\n##### 2- Continuous distributions\n\nWe will begin by explaining discrete distributions, but first we want to understand three concepts that will help us understand probability distributions. \n\nThese concepts are:\n\n###### 1- Probability Mass Function (PMF)\n\n###### 2- Cumulative distribution function (CMF)\n\n###### 3- Probability Density Function (PDF) ","metadata":{}},{"cell_type":"markdown","source":"if We want to know what is the probability of finding a house with a certain number of rooms if we collection this data again or deal with population data based on sample data\n\nWe can use PMFs or Probability mass Function","metadata":{}},{"cell_type":"markdown","source":"## What is Probability Mass Function (PMF) \n\nprobability mass function (PMF) used to represent a distribution , which maps from each value to its probability. A probability is a frequency expressed as a fraction of the sample size, n. To get from frequencies to probabilities, we divide through by n, which is called normalization . It is used with disceret variable ","metadata":{}},{"cell_type":"markdown","source":"We will now work on Boston homes data. \n\nFor example, we want to see what is the probability of finding a house with three bedrooms\n\nNote : \nIf you are working on your own project on your own device. you can use Pmf from empiricaldist package . Like this","metadata":{}},{"cell_type":"code","source":"#fig, ax = plt.subplots(figsize=(12,8))\n#pmf = Pmf.from_seq(df_house['BedroomAbvGr'])\n#pmf.bar()\n\n#label_graph(18 ,'Number Of Bedrooms' ,  'PMF' , 'Probability of each room' , 20 )","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"in the pervious picture you can see that the probability of finding house with 3 bedrooms around 55%","metadata":{}},{"cell_type":"markdown","source":"if you are working on kaggle you will not be able to use this package because Kaggle does not allow installation of this package \nDon't worry there is another way to know the probability by using seaborn ","metadata":{}},{"cell_type":"code","source":"sns.set_style('white')\nfig, ax = plt.subplots(figsize=(12,8))\n\nprobabilities = df_house['BedroomAbvGr'].value_counts(normalize=True)    \nsns.barplot(probabilities.index, probabilities.values)\n\nlabel_graph(18 ,'Number Of Bedrooms' ,  'PMF' , 'Probability of each room' , 20 )","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"PMF has limitations in dealing with many unique values. In the following picture, you will see that there are many bars and you cannot determine the probability of each value, so if you want to deal with a column that contains many unique values or with continuous values such as prices, areas ... etc., you can use cumulative distribution function (CDF)","metadata":{}},{"cell_type":"markdown","source":"## 2- Cumulative distribution function (CDF)\n#### What is Cumulative distribution function ?\n\nCDF is another method to describe the distribution of continuous variables. The advantage of the CDF is that it can be defined for any kind of variable (discrete, continuous, and mixed).","metadata":{}},{"cell_type":"markdown","source":"if we want to know what the probability finding house with Sale price 100,000 or less \non your own device you can use Cdf from empiricaldist package Like this :","metadata":{}},{"cell_type":"code","source":"#fig, ax = plt.subplots(figsize=(12,8))\n#sns.set_style(\"whitegrid\")\n\n#cdf = Cdf.from_seq(df_house['SalePrice'])\n#cdf.plot()\n\n#ax.annotate(\"25% of houses <= 129900$ \", xy=(140000, 0.24), xytext=(150000, 0.06) , fontsize = 18 ,\n            #arrowprops={'arrowstyle': '-|>', 'lw': 2 , 'color' : 'b'})\n\n\n#plt.plot(129900 , 0.25 , marker = 'o' , color = 'r' , markersize = 15)\n\n\n#label_graph(18 ,'Sale Price' ,  'CDF'  , \" \" ,  20 )","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"As you can see in the graph above, we have a 25% chance of finding a house that costs $129,900 or less.","metadata":{}},{"cell_type":"markdown","source":"For Cdf and Pmf in empiricalcdf package there is a great feature for example if you want to know what is the probability of a certain value you can pass this value to the variable cdf or pmf that you created earlier. And vice versa, that is, you can pass the probability and see its value , For example","metadata":{}},{"cell_type":"code","source":"#print('The probability of 100000$ is : ' + str(cdf(100000)))\n#print(\"The value of probability 25% is : \" + str(cdf.inverse(0.25)))","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"There are two another way to plot Cdf one using function and other using seaborn ","metadata":{}},{"cell_type":"markdown","source":"Cdf using function : ","metadata":{}},{"cell_type":"code","source":"def cdf(data):\n    \"\"\"Compute CDF for a one-dimensional array of measurements.\"\"\"\n    # Number of data points: n\n    n = len(data)\n\n    # x-data for the ECDF: x\n    x = np.sort(data)\n    \n    # y-data for the ECDF: y\n    y = np.arange(1, n+1) / n\n\n    return x, y","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig, ax = plt.subplots(figsize=(10,6))\nx_price , y_price = cdf(df_house['SalePrice'])\nplt.plot(x_price , y_price)\nlabel_graph(18 ,'Sale Price' ,  'CDF'  , \" \" ,  20 )","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig, ax = plt.subplots(figsize=(10,6))\n\n# Cdf using seaborn :\nsns.ecdfplot(data=df_house, x=\"SalePrice\")\n\nlabel_graph(18 ,'Sale Price' ,  'CDF'  , \" \" ,  20 )","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 3- Probability density function (PDF)\n#### What is Probability density function ?\nThe probability density is a function that assigns the relative likelihood to each possible outcome . we will work on it later ","metadata":{}},{"cell_type":"markdown","source":"#### Great, now let's explain discrete probability distributions","metadata":{}},{"cell_type":"markdown","source":"# 1- Bernoulli Distribution \nThis distribution is related to Binary classification . (i.e What is the probability that this person is sick or not? Or what is the probability that this customer will buy the product or not and so on)","metadata":{}},{"cell_type":"markdown","source":"In titanic dataset we want to know What is the probability that a person on the ship will survive?","metadata":{}},{"cell_type":"code","source":"sns.set_style(\"white\")\nfig, ax = plt.subplots(figsize=(12,8))\n\n# calculate the probability for each class \n\n# perform Bernoulli Distribution using empiricaldist package \n#pmf_survive = Pmf.from_seq(df_titanic['Survived'])\n#pmf_survive.bar() \n\n#another way to perform Bernoulli \nprobabilities = df_titanic['Survived'].value_counts(normalize=True)    \nax = sns.barplot(probabilities.index, probabilities.values, palette='PuBuGn_r')\n\n\n# to write percentage on the top of bar \npatches = ax.patches\nfor i in range(len(patches)):\n    x = patches[i].get_x() + patches[i].get_width()/2\n    y = patches[i].get_height()+.001\n    ax.annotate('{:.1f}%'.format(y), (x, y), ha='center' , fontsize = 18)\n\n#plt.locator_params(integer = True) \n\nlabel_graph(18 ,'Survived' ,  'Probability'  , 'Bernoulli Distribution' ,  20 )","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"0 refer to Not survive \n\n1 refer to survive \n\nThe probability that a person will not survive is higher than the probability that he will survive","metadata":{}},{"cell_type":"markdown","source":"# 2- Binomial Distribution \n\nThe binomial distribution is the discrete probability distribution of the number of successes in a sequence of n independent experiments . it is frequently used to model the number of successes in a sample of size n drawn with replacement from a population of size N","metadata":{}},{"cell_type":"markdown","source":"Let's explain that defination \n\nIn any experiment, the outcome of this experiment is either success or failure, and in the probability distributions, we are the ones who determine success from failure according to what we interest \n\nfor example, If we take a random sample of 10 people who survived the Titanic, what is the probability that we will find 3 or 4 men in this sample?\n\nIn this example, I am interested in knowing . What is the probability of finding a certain number of men in the sample that i drew? This is considered success for me, and failure is that the sample contains women.\n\n#### The probability of success = p\n\n#### the probability of failure is 1 - p ","metadata":{}},{"cell_type":"markdown","source":"Mathematical Formula for Binomial Distribution is : \n\n![mod8-binomform.png](attachment:mod8-binomform.png)\n\nWhere :\n\nn : Sample data\n\nx : The number that we predict (We want to know what is the probability of finding one or more men in the sample)\n\np : percentage of  the success that we have determined based on what we care about (here we care about men) in population data","metadata":{},"attachments":{"mod8-binomform.png":{"image/png":"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"}}},{"cell_type":"code","source":"survived = df_titanic[df_titanic['Survived'] == 1]\nsurvived['Sex'].value_counts(normalize = True)","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"n = 10      # sample data\np = 0.31    # percentage of male in data \nx = np.arange(0 , 5)\n\nfig, ax = plt.subplots(figsize=(12,8))\n\n# calculate and plot binomial distribution\npmf = stats.binom.pmf(x , n , p)\npps = plt.bar(x , pmf)\nprint(pmf)\n\n# write percentage on the top of bar \nfor w in pps:\n    height = w.get_height()\n    ax.text(x=w.get_x() + w.get_width() / 2, y=height+.0001 ,\n            s=\"{}%\".format(round(height ,2)),ha='center' , fontsize=20 , color = 'r')\n\n# convert x-axis from float type to int type\nplt.locator_params(integer = True)\n\n# label the axis\nlabel_graph(15 ,'Surviving men' ,  'Probability'  , f\"Binomial Distribution(n = {n} , p={p})\" ,  20 )","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 3- Multinomial Distribution","metadata":{}},{"cell_type":"markdown","source":"In a binomial distribution we always have two classifications (we can say that it is a Bernoulli process) and we are interested in knowing details about one of the two classifications (that is, we were interested in knowing the number of men in the sample)\n\nBut what if we want to know the probability of more than one event occurring?\n\nTo take an example, we will work on data that record traffic violations, and in this data there is a column that contains the gender of the person who committed the violation (black - white - Hispanic - Asian - other)\n\nFor example, if we draw again a random sample equal to 10, what is the probability that in this sample there will be 5 white people, 2 black people, and 3 Asian people ?","metadata":{}},{"cell_type":"markdown","source":"#### Calculate the percentage for each gender first ","metadata":{}},{"cell_type":"code","source":"df_police['driver_race'].value_counts(normalize = True)","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"##### Note the order in the elements x and p, the first element in x is the number of white people, the first element in p is the percentage of the number of white people in the data, and the sum of the elements of x must be equal to the random sample","metadata":{}},{"cell_type":"code","source":"stats.multinomial.pmf(x = [5 , 2 , 3] , n = 10 , p=[0.7 , 0.14 , 0.02])","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 4- HyperGeomatric Distribution\n\nBefore diving into the hypergeometric, we have an important question that we want to answer.\n\n##### What is the difference between Binomial and hypergeometric distribution?\n\nThe main difference between both distributions is the principle of replacement . \n\n##### What is the principle of replacement ?\n\nSuppose we want to calculate the average weights of students in one of the universities the number of students in this university is equal to 10,000 students (population data), we will take a random sample of these students, suppose that this sample consists of 10 students. I return the first sample to the population data and draw another sample (I may get the same students again in this sample) and this is the principle of replacement. I have the ability to take a sample of the population data and return it again to it\n\nIn the case of without replacement, if I took a random sample from the population data, I cannot return this sample once\nFor example, if we take a random sample of people and find that some of these people are infected with the Corona virus, will we leave these people and do the experiment again and take a new random sample of people, or will we place these infected people in quarantine? We will definitely isolate them. This is a hypergeomatics distribution\n\nLet's summarize all of this before we do practical this distribution if you are just exploring on your data for example you want to know how many men in the sample , how many men survived the sinking of the Titanic or how many female employees got promoted in this position we will use the binomial distribution. But if you are going to take action based on this sample, for example, you withdraw the driver’s license from people who use drugs, or you isolate people infected with AIDS or Corona virus, in this case we will use the hypergeometric distribution\n\nLet's explain this distribution on our data. In the Stanford Police Project's data, there is a column called drugs_related_stop. This column is recorded as whether the person is a drug addict or not. In this situation, we are supposed to apply a penalty to the abuser, whether by withdrawing the driver's license or applying a fine or imprisonment, so we will use a hypergeometric distribution\n\nFirst, we will calculate the number of people using and not using drugs, from which we see that the number of drug users is 815","metadata":{}},{"cell_type":"code","source":"df_police['drugs_related_stop'].value_counts()","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Second, We use the hypergeometric function in scipy, and its parameters are\n","metadata":{}},{"cell_type":"code","source":"x = np.arange(0, 8)\np = 91741 \nN = 815\nn = 10 ","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Where :\n\nx : is the number of people we want to predict (we want to know how many people in the sample are likely to be drug users)\n\np : The population data\n\nN : is the number of successes in the population (drug users)\n\nn : Sample data","metadata":{}},{"cell_type":"code","source":"fig = plt.figure(figsize =(15 , 8))\nax = fig.add_subplot(111)\nax.grid() \n\ngeom = stats.hypergeom.pmf(x ,p , N, n)\n\nax.plot(x, geom, 'o' , color = 'b' , markersize = 15)\nax.vlines(x, 0, geom, lw=3 , color = 'black')\n\n# label the axis\nlabel_graph(15 , 'drugs related stop' , 'hypergeom PMF' ,'Hypergeomatric Distribution' ,  20 )","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 5- Geomatric Distribution","metadata":{}},{"cell_type":"markdown","source":"###### Geomatric distribution : \nis a probability disceret distribution represent number of failures before you get a success in a series of Bernoulli trials (success or failure of the experiment) Once again, you are determine the success or failure of the experiment\n\nIf we want to know what is the probability of Cristiano Ronaldo scoring the second penalty kick. In this situation we can use the geometric distribution","metadata":{}},{"cell_type":"markdown","source":"The equation for this distribution is:\n![download.png](attachment:download.png)\n\nWhere :\n##### n = Number of trial \n##### P = Probability of success \n\n\n","metadata":{},"attachments":{"download.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"Cristiano Ronaldo has a penalty score of 0.83 (p = 0.83)\n\n![100-160828-benitez-real-madrid-cristiano-ronaldo-2.jpg](attachment:100-160828-benitez-real-madrid-cristiano-ronaldo-2.jpg)\n\nWe will also see the possibility of Cristiano scoring the third and fourth kicks","metadata":{},"attachments":{"100-160828-benitez-real-madrid-cristiano-ronaldo-2.jpg":{"image/jpeg":"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"}}},{"cell_type":"code","source":"sns.set_style('white')\nfig, ax = plt.subplots(figsize=(15,8))\n\nfor number in range(1 , 5):\n    probability = stats.geom.pmf(k=number, p=0.83)\n    pps = ax.bar(number , probability , color = 'b')\n    ax.locator_params(integer=True)\n    \n    \n    for p in pps:\n        height = p.get_height()\n        ax.text(x=p.get_x() + p.get_width() / 2, y=height+.002 , s=\"{}%\".format(round(height ,2)),ha='center' , fontsize=20)\n\n        \n# label the axis\nlabel_graph(15 , 'Penalty kicks' , 'Geomatric PMF' ,'Geomatric Distribution' ,  20 )","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"As you can see, the probability of Ronaldo scoring the second penalty kick = 0.14%","metadata":{}},{"cell_type":"markdown","source":"## 6- Uniform distribution : \nWhen all events have the same probability of happening, then our distribution is uniform distribution \n\nFor example, the probability that you will or will not be accepted for a new job or a new scholarship is 50 to 50.Also, when a dice is thrown, the probability that each of the six faces of the dice will appear is equal 1/6 (0.16%)\n\nyou can perform this distribution using Pmf from empiricalcdf or using seaborn\n![291894673_3249131698634746_8966299531093562284_n.jpg](attachment:291894673_3249131698634746_8966299531093562284_n.jpg)","metadata":{},"attachments":{"291894673_3249131698634746_8966299531093562284_n.jpg":{"image/jpeg":"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7- Poisson Distribution\n\n#####  Poisson distribution :\nis a probability disceret distribution that is used to show how many times an event is likely to occur over a specified period\n\nIf we want to know what is the probability that a traffic officer will stop a one or two or more drivers over a specified period of time (assuming throughout the day), in this case we will use the Poisson distribution\n\nPoisson distribution equation is : \n![unnamed.png](attachment:unnamed.png)\n\n##### Where :\nμ = 1 / λ (average number of event)\n\nx = (the number of event)\n\ne = 2.71828 (e is Euler’s number, a constant)","metadata":{},"attachments":{"unnamed.png":{"image/png":"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"}}},{"cell_type":"markdown","source":" We will work on such data Stanford Open Policing Project dataset\n###### Step 1 :\nwe filter the data to include from 1/10/2005 to 7/10/2005 ","metadata":{}},{"cell_type":"code","source":"police = df_police[(df_police['stop_date'] >= '2005-10-01') & (df_police['stop_date'] <= '2005-10-07')]\npolice.tail()","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"###### Step 2 :\nWe combine the date column with the time column and make them into one column","metadata":{}},{"cell_type":"code","source":"police['Stop_date'] = police['stop_date']+ ' ' + police['stop_time']","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"##### Step 3 :\nWe convert Stop_date column type from object to datetime64","metadata":{}},{"cell_type":"code","source":"police['date_time'] = pd.to_datetime(police['Stop_date'] , format = '%Y/%m/%d %H:%M')","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"##### step 4 :\nWe add two columns to the data set, a column for the time when the stop occurred, and a column for the day","metadata":{}},{"cell_type":"code","source":"police['Hour'] = police['date_time'].dt.hour\npolice['day'] = police['date_time'].dt.day","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"A note on how to calculate the average of events in a given time period.For example, if you want to calculate the probability of an earthquake in the next year and you have historical data about this event, you will calculate the average earthquakes in previous years (by calculating the number of earthquakes that occurred in each month of this year) and then make a prediction\nAlso, if you want to calculate the probability of a particular event occurring in the next month and you have historical data, you calculate the average of events in each of these months (by calculating the number of events that occurred on each day of this month and calculating the average of events in this month) as We did now","metadata":{}},{"cell_type":"markdown","source":"###### step 5 :\ncalculate the number of stops for each day and change the name of the hour column to stops","metadata":{}},{"cell_type":"code","source":"stops = pd.DataFrame(police.groupby('day')['Hour'].value_counts())\nstops.rename(columns = {'Hour':'Stops'}, inplace = True)","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"###### Step 6 :\nCalculating average stops for each day","metadata":{}},{"cell_type":"code","source":"stops.groupby('day')['Stops'].mean()","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"As you can see that the average stops per day is 2 (of course we round the decimal numbers to become a integer number)","metadata":{}},{"cell_type":"markdown","source":"###### step 7 :\n\nperform and plot poisson distribution","metadata":{}},{"cell_type":"code","source":"fig, ax = plt.subplots(figsize=(15,8))\nax.grid()\n\nnumber_of_stops = np.arange(0, 6)\npoiss = stats.poisson.pmf(k=number_of_stops, mu=2)\nprint(poiss)\n\n\nax.plot(number_of_stops, poiss , 'o' , ms = 15)\nax.vlines(number_of_stops, 0 , poiss , colors='Black' , lw = 3)\n\n# covert x-axis from float to integer\nax.locator_params(integer=True)\n\n# label the axis\nlabel_graph(15 , 'Number of Stops' , 'Poisson PMF' ,'Poisson Distribution' ,  20 )","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Great effort, now let's talk about continuous probability distributions","metadata":{}},{"cell_type":"markdown","source":"# 8- Normal distribution\nThe normal distribution is a continuous probability distribution that is symmetrical around its mean, most of the observations cluster around the central peak. in Normal distribution the mean is equal to median . it's also known as the Gaussian distribution","metadata":{}},{"cell_type":"markdown","source":"In the following graph, you can see some shapes of data and and properties of each shape 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inpmPfcnLs4WFhYaGhpKSEh8fn/7+fnYwIyPDycnp9u3bAwMDVCUGiHhmufZGsj5J5Flw0jHimdz2Jft8Y1FREVy0gwcPDg0NsYNtbW1A2tGjR/fu3Ts4OKj2xJWVlfHx8RGSiu6Pjxbd7X3ueL0cPHshsmH3uaaJsVEqZ7WanZ0lnpEM41nk+QPEM8vmGVuguby8HBgYmJ+fL/xpenraw8OjtrZW7Ylra2tg4SxJRSuLc6WNIzL5Zy9E1jucb1mcn6NyVit9p8eJZ8Qz4pn18KysrOzs2bNVVVUuLi51dXW9vb0DAwPDw8M1NTXAm6enpyb/jKRFEucbl0s+QfON5mZv0jU3N9fd3Q2TgY3Q+xvNWcQz87EveXkGdJ0/f/706dMVFRX499KlS7dv34ZPhiOxsbGNjY1UJQZIJ892xBTDckaKHiKemZu9SVdTU9OhQ4cOHz785ptvXrx4kQrTbKUXz7Iz3iSeyWdf9PyZ5Uknz+xiC4ln5mlv+gpemqenZ1VVFRWm2UovnqWlvUc8k8++iGeWJ+KZ5dqbviopKQkODtYSYGVlZdnCtb62qliXd5Mv8asryxMzC3LzLLSwW6FYtZwqVSM0VOIZiXhm0zyDc3bhwgVNv66trY2NjfX19fVbrAYHBi7fbkkvu5d5Xc1Wfc0PLbn76q/V/ipxy7nRJF8JDQz0t3b1STGu08nuhvHstyfqA3JaxoYHLLeW0UTHx8fp/Y0k4pnt8qy+vn7fvn0TExPWXUruWZ2/PFr/2xMNqtvRsw98mpKsX6n9Vcr23PGGl0/dW1lbly/9EucbQTKab5TbvohnliedPHM8cwGW05r/DeKZudmbXoqPjz9z5ozVl5JPTidcEOOuCeTb1qiGN2KJZ7ZiXxvi2erqak9Pj74To/Pz81euXMnKyuro6KAqMUA6ecberNOY9zjxzNzsTS8ZfX7GPEU8I54Zy742xLPFxUUfH5+QkJD8/Py1tTWJZwFmERERGHt6e3tPTk5Sregr4pnl2htJVTbFs9jk/cQz+exro/ONo6Ojubm5INPu3bsPHz7c2tqq8x0KYFhfX19lZaWXlxdOp1rRV8Qzy7U3kqpsimfIEfFMPvvaKM/GxsZqa2ujoqLs7e39/f337dt37do17aeMj4/HxMQAgbGxsZo+JL+6ujo9PT1pmZqaur84Ny3TpliaKbs39Jtj9TLxbM/5ltXFGfnSPz87ZaHVCun7TULi2QZ5Bm8GLflC5mvEM2onsvMMNPLz83N2ds7IyGhsbIRnBsdreHhYyrmgmouLS0NDgyaeTU1NTVigpu9P1ncM+qXXH8xqkGMLzm7Yl9zwYpTuL1PUXPyR3sZ/suGNmIag7AaZEu+fUR9b0ooissSahYhnJuaZwfeczJBnGenbiGdmzbO1tbWWlpbR0dH19XXsz83NSbmLlpube+fOnfr6+r1797a3t1tfKdf2zf7iSJ3BK4x1bs9H6jCAw2dDDZ6l2XqyQb6U/+po/f6MDptY5CDBoHQu90CA+fl5mJUcz6Kaj2yEZ7BH4pnc9rUhnsHS3Nzc2Mfg29raPD09pdwPq6mpCQkJCQgIsNa3+NT3z6IJGmyBG982ftdBpu13J+o9s2xoUasWg1paWjp16lRlZeXIyIhasGFoePbsWdiXj48PTMaKS4l4Rjwzln1tlGeOjo53797FPuDk7u4+Pj5OpUw8I57pNCjgKjs728vLy9XVNTMzs7q6enFxURgADHNxcbEFgyKeEc+MZV8bnW+Mjo7eu3evn5/fzp0709PTqYgVxDPimWSDun//fkpKymuvvfbGG2/AiOrr6/lP5eXlb7311oEDB4KCgtgUiFqtW7iQBe+czt/JzLPl1TWFXOlfn15Ykc6zkKRwg3jWYx11bdY8Uyhfh4qhZWpq6u3bt4lkxDPimUSDwljw3Llznp6e3t7eMTExnZ2dhYWFQiO6du3aoUOHxsbGTp06hZCaIhkZGenu7u6xWA3197qmNv0uUtuawHOp9obz7GTDa6cbO7vkSn9vb09Te/fvJfPMNyFW3yzAefXPbh4e6LXcWkYTRUu2gPc33rt3LysrKzk5OT4+vqCgQN8FYMQz+XhmwJeWiGcm4xkGgjk5OcXFxTMzM2oDVFRUeHh4zM3NZWdnR0dHW3EpaZlvvJT1vGFzdGY732gAz2i+Ubp9bfT9IPv37z9w4MCxY8fCwsJSUlJmZ2eplDedZxufpSGeyWRvXEtLS6mpqez77ENDQ0lJSffv3xcGwNAwJCQE9rVv377W1lYrLiUtPDP4nhPxzDbta0M8g8n5+PjcunVLU4C1tbX29nYE6O39qD4mJibq6+tv377d2NgougduHSKeEc90GtT8/LyDgwO7YdbW1ubs7AyqicLAORsZGdHkwFmNbIRnjXmPE8/ktq8N8Wx5eRmDR3t7+wSlCgoKYIHCAE1NTb6+vkeOHMEwk5trVlbW+++/HxcXl5OTY5W2Sjwjnuk0KNiOt7d3ZGRkRUVFWFhYaGiopnflWL2IZ8QzY9nXRtc3Njc319bW3lKqpaVF9PLGyclJDDBnZ2eBvatXr7KD4FlQUJAVvzuceEY8k2JQHR0dERERjo6O4eHhEt+qY5UinhHPjGVfG10PMjAwkJSUVFVVhdEl0LW6uqoapr293cnJqauri/1bVlbm7u6OIwcPHpyamlIbLUi5sLAwZ4FaWZy/3T7+3PH6TefZRlaFycczt4y2laV5S6xZSOe7tvXi2crKCswHo0CYxv3799XaDvHMynjmGpdMPDNTnsG84Wm98847p06dgqPm6uoKpInC4Ii3t3dlZaXo+NjYmIuLS2NjoyZTR4ChoaFhS9PE2EhZQ58m+zTNdiHztQ32AjJtz0fW709tnhwbsbhqZdJ3uZP29fonTpzYvXv3nj173n///dDQUNF6EOIZtrKcn6Ml+ydGWw3P7GILiWdmyjOYt6enJ5B25swZ8MzNzU30viv86+XlVVJSwgx4VSnsrK+v9/X17du3T8uDoparTZ9v3PioluYbZbI3roWFBScnpytXrmDA19/fD0sh/8yIc3TEM9u0r41+nzoqKgr+2f79+52dnVNSUkQBqqurd+3a5ePjA3TduXMnNTW1qKjo2rVr8OTgnBUWFlplKRPPiGc6DQq2ExAQcPz48aGhobGxscnJSdG7vBsbGwE8WArGi9b9JXfiGfHMWPa10ftnsMOcnByAKj8/f2JigopYQTwjnkkwqJWVlVOnToWHhx8+fBjESkhIEN1LvnXrlqenp6YbzNYkG+HZUNEXiGdy29dG/TP4W9nZ2RcuXMjKyqqoqND3hrlVinhGPJNiUDCWtrY2TSsbq6ur33nnndDQ0IyMDOt+TYGN8Gyk6CHimdz2tdH1IIcOHXJzc3N3d3/33XcjIiJEz5/ZpsyEZ4GJkcQzc7M3rvX19cTExLfeeisuLq6np+fo0aOiV+kvLi729fXV1dU5ODho+ua71b+/0Qg8M5v3NxrMM3p/o4l4JtTNmzcDAgLofVfmwLPq3H/bYC9APJObZ/Pz856env7+/qdPn25tbXVxcWHvvhJpdXU1LCwsNzdXy1Ws+P36jGf74tI26J+Zw/v1Gc/eO11qkH9m8e/XN419bXS+sbCwMDMzMycnB84ZjJN4Zg482/iolngmN8+WlpZgL05OTsBVfHw8/oo+Qt3Z2Xny5EmYlbe3t+pjMNYkLfONvYX/aJhPY7bzjQZkgeYbpdvXRucbMbo8fPgwrPHYsWOwQClntbe3+/j4ODg4AIRWWcrEM+KZFINqampydXXdt28fiFVXVyf6dWpqqkEp1fc6Wpm08MzgOTrimW3a14Z4Bi+yq6urRSCYqM5XMlZVVd26dQsn2tnZgW3WV8rEM+KZToOC7QwPD3d0dMAE8BcemGi9vu2IeEY8M5Z9bYhnKysrBw8efPvtt3fs2LFt27YdSpWVlUk5Fzbs7Ozc09NjfaVsJjzziE8inpmbvXEtLy/7+PjAXnbu3AnbiYqKstm5ehvh2XLJJ4hnctvXRr9/5unpmZeXNzU1lZ6e7u/v39nZKcUsl5aWQkJCtMw3YvS6urq6IpsWllfQCuXYFlfWbnZNmwPPNtILyMczt8yOpdV1mQp/dlHGNgPp60Jp98/6+vq6uh4svDt37hzMYX5+nnhmxTxDRohnZs0zWKCjo+O1a9fAsNLSUg8PD9GaY7VaWFiIjY3NyMjQEgZ9x9DQUG9vb58MGh3qP1vW/ptNfWWwrNvGewFL3NBzvRXbKEuL+VDT09NG5Nno6Ch7OQh7Y47Nvo5AJ892xBQTz4hesvMMys7O3r17t7u7u52dXVZWlpQB7MWLF3/729+eOXMmKipK7RplE+hi3dizR+uIZ9a0vRjV8E5ck1l9hUj7fGNwcPB+pTAohFGoDVZWVnbp0iXrfqxTJ882OMoxH56tlvwP4plZ82xpaamjo6O1tRWjV4kfm8awtKWlpb6+vra2drMMlXhGPNtcnsE/6+npYetBent71b5Yp7+/f9euXfb29ta9xFELzwz2acyTZzBM4plZ8+zu3bteXl4YXQ4PD8NXs5TvTRPPiGeby7PV1dW4uDgfHx9fX98DSnl4eNy5c0cY5uTJk2fPnnV3d7fur30Sz4hnZsGzhYUF9iRZTEwMXC43NzdLefDTFnj2h+ha4pnZ8mxlZQUMCwwMxCgQO87OzsnJyc3NzTzAzZs3o6KiBgYGwDnRZ5iIZ8QzkvF5Njc3B+fMz8/v9OnTdXV1MLzJyUni2aZv05f/zwZ7AeKZ3DzDWHD//v01NTUK5YPVQJrwe57sa5979+49ePDgq6++Ck9O7WQ+go2Njcm0bMo0Ghnsd01r/l2kXDzD9nJ0Y1B+d3CBXFtAXpfONGw7XWYwzwD7gJyW0aF+y61lNNHx8XFzf38j0peRkfHuu+/a29vv2rUrPz/fUsBu3TwzSi9APJOVZ6urq4cOHcIQMDY21s3NLTQ0VHgvGZY1OzuL0WFLS4udnV1bW5umS8j6WIsJBCh7Z3f87kS9rC0ZLo58228lPJxjF1u4Ef8srKgbBWXRFS3H52qNzDMMD2/cuAGMlZSU3Lx5E0NO4hnxjHgm0aDgkGVnZ587dy4zM1PTig9QzYJuSxsm7fON9y9/1goa5wZ5RvONpuDZ/Py8u7t7Y2OjljD19fUYh966dYsfAfn8/f39/Pyio6M3a36SeEY8MweeXbx4EeYDz6ypqUni8mDb4dkbp24azADiGfHMkPcR79+/38nJKSYm5uTJkxhIil4O0tvbGx4ebmdnl5eXxw9iNAqewYaBw816Z53V82yh+H8Rz8yZZ6urqxEREW+++eapU6c6Ojp8fX2t+yX6BvBsIwwwT5415j1OPDNfnq2srGCAmZaWdu7cuaSkpMLCQrXPkwUEBIh4tmvXLvytqakhnsnEM+voBayYZ+z7Z0FBQRgLtra2WtDaYOIZ8cwKedbY2Hj37t2ZmRmMLrXf6xPxbGhoqKqqKiUlxd7eXsv7iGX9stzFWqvl2XunS22ZZ2vm9E1C7ev1jxw58v7774Nqhw4dioyMlOmbh8Qz4hnxTLeSk5PPnDlz7949f39/7bfBDh48WFBQIDo4PT3t4eFRW1urydoHBwdl+pD88EBv0tU2a31/ozX1Anpt7P2Nsn42fmpqylg8g+CWRUREBAcHA2b9/f022yvZAs/2xaURz8yaZ3CwTpw4UVpa6u7uDqr19fUNDw+LHLWxsbFLly5t374dLhrcsjt37jQ1NbW1tV28eBEsBAg36x2sVjzfaLM8s6z5xsXFRbhlLS0tms7FkA6jvcLCQhiXLfOsq+DLVtA4fRNiiWdmzbOsrKw33nhj27Ztr7766o4dO957772wsDDRAHZ8fLy4uPjKlSug2sDAQE1NDQy4o6MjLy8PHltv76ZVEvGMeLa5PFteXvbw8IiOjsYg7+bNm4DW0tKSMACOHDx4MDEx0cXFZRMtZdN5ZhgDiGfEM/14Nj8/P6QU3LLBwUHgCvSylG/sWj3PmvIeI56ZM8/gfgUHBzs7O4Nqrq6uJ06cEE3az8zM9PT09PX1IYz2R2KslWce8UnEM+KZiXhm0bJinu2OzbOaXsBaeTYxMTE6OgoXDQxbXV1Vu9hkbm7u3LlzXl5ehw8fts3nqTfCAPPkWVnOz4lnxDPimYlGgsQz0/DswoULZ8+e7ezsjIqK0r7GBMzz9/fX9CY5UBBEHBwcHLJYTYwOu6W3/M42eFaa/SsDzgXsAy+0To4NW24to4nev3/f3N/fSDwjnhHPDOBZSkrKqVOnGhoa+LvzVSfqq6urS0tLx8fH3dzcsKOJZ4uLi/OWrNXlBa+sduKZVv+sPqSga33FsitadHuYeEY8I55ZCc9SU1N37tzp7u7+1ltvBQQEBAYGJiYmTk9PC8N0dXWFhIR4e3unp6dbtzFqn2+su/h9K2icwUnHNsAzmm80b541NjYmJSXR+kb5eFad+2/EM7PlWXt7OyiVlpaWkZGBv3DXrly5YkGv8zYlzwxjgLltkecPEM+sk2eAmZeX1/bt26uqqohnZjWzQTwzDc9IUnjmnxhNPCOemTvP1tfXZ2Zm3NzchC/dJ54ZawtJCieeEc+sgGcbYQDxjHhmOvNbWFhwdXXVwrOVlZWp+xP3J0bl2Banx9Iru39zzDrfd2VNvYC+PHv7zL1JedoM2+bmZolnxDODrTI7403imXXyzN3d/fbt21rCnC3vsYuv3Xu23uib07n69+Lq0f0Rz6xsezm6QY4Gw7Y9SXWjU/PEM+KZwVaZlvYe8czaeDYxMXHz5s3333//3LlzWhZxHi3p/2VE3fORDXJs1gozG+cZNpkaDDb0uaOzyybj2fr6em9vb21t7cDAAPGMeEb0MlOetba2JiQkJCUlxcfHa/nm04kr/b85ZrWfKJPbcjLSt1FRGHs+s37MhDxra2vz9fUNCwvbv3//8PCwzfLMsDk6c9tOJ7sTz6yTZxJFPDP9SJA28+HZxMQEPLP5+XlXV9fi4mKb5Zl1tGTkgnhGPCOe6b2lpO0gnlkBz5h6e3udnJxaW1s1BVhaWpL1tQ7LSwuK1SUZN8WKT3aHWp7FpzgRzz7gWVE3CkrWilhaXKD3gxDPrMpyaDMrno2Pj/v6+l69elVTgLW1Nbhx8r2/cWxkuKK+K+ZSQ3xxo0xbUknj9nj197OtqSVvJC8vRDY4JDWcvdIoXy2giqubukdHhuV7f+Pk5KRNv7+ReEY8s/H5Rn9//8LCQoVybchmmWHGndGfhtc9d6JBvk3T4izr41ls8n5D216DrFXws/C6kqZJM+n5iWe0iS0nKWUPFYVF86ympub999/39vbet29fRUXFZplhzt3RzXrzgPXxLPL8AfNM3rPH6kqbiWcSVFdXl5mZWVlZyedPe3p6MOrMzs6+cuXK3Nwc8cymLId4ZlnadJ5Zx8iMeGYNPOvu7t6/f//Zs2f37t17584ddhB4c3BwuHz5MiA3Pz9PPDPulpG+jXhGPLManllHSzZzqySeSVJBQcGRI0fYDv/sBXjm7e09PDy8uLio5VzimWFbafaviGfEM+IZWSXxzMjml5eXx25oX79+PTQ0lE053r17NyIiwsvLy93dfWxsTMOp6xGXu587TjwjnpkRzwYmbO79jZvIM2tqycQza+BZfn5+XFwcdq5cuZKQkCD8aXJy0tXVtb6+nnhGvQDxjHhGPCOemTvPbty4YW9vD2j5+fmVl5fPz8/PzMzMzs6Ojo7CS9u/f39XV5emc2m+cSOW458YTUVhdJ6ZeL5xdXV1ampKjgdRiWebkpeQpHDimQXzDPRKTEz09fXNzs7Gv2lpaaWlpRUVFQFKaf+eJ/FsI5bjmxBLRWHRPJubmzt//vxbb72Vm5tLPCOrJJ5tPs82IuKZYdut3KeIZ1bAs4mJiatXr3p5edk4z6yjJRPPiGfEM0O2xrzHiWdWwDOmgwcPXrhwQUuA9fU1hUK+DTwbIZ7ZBs8mlA1KrrakbKjEM+pJiWfEM804a+ocyCm/d7GiSY6tqKopOOfe705sToFXXvhPq2nJZm6Vv4tsiMi7V1jVJFNDQhNt7x0inhHPDLQc17hkKgor4FlQUJD2+ca8uvGfhdf99kSDTNsLkcQAm8iL8ou1cm3PHKkrb5uyWp4tLi7OzMysrKwQz2SyHLvYQioKi+ZZd3f3oUOH3n333V27dt2+fVtTsIKG8c2aDyQG0KyJxA09eUW7lfJsenraw8PD0dHR39///v37xDPiGfFMVWtra+yrURj8aRn5Ec8sKC82O2tizTxLSko6cuQIrDQ4OLi2tpZ4ZtxtqOgLxDMr4JlEWT3PnM5k0iiTeGa+PDt16hSbPzl//nxaWpqmYEdL+n8ZUfd8ZANtem0jRQ/BcrafLqSiMO722xP1o8QzYgDxjHgm1OnTp9m79sGz5ORkTcESr/fsiKt1SKqnTa9t/PIDnh04X0BFYdzNPrFudGqeeEYMIJ4Rzz5SfHz8sWPHVlZWDh06VFNTozYMfr0/MT45NkKbvtta+edhOZOjA1QURt/m5szu/Y1WzLP+wkeshgE2fhfAmnlWV1dnZ2fn7OwcFRWlfYkjyRBVfBGWQ8VgDtqgQeXm5np4eJw8eVLLsikr5hmbObcOBlhTXohnYs3MzIyNjWn//hnJQDW+oLj7YyoGS+fZnTt3MOZraWkJDAy8dOkS8YzyQjwzU56RSMQz7QLDYmNjFcpvB7Id2+TZe6dLKS/EM+IZiWTBPCsqKrp48SJ2Kisrg4ODNU1mFNSP/zqidmtUvfVtjAGUFyvYnj1aSzwjkWyXZ8XFxSEhIdgpLCxMSUlRG2Z9fa1vYKimqb2uucP6tqVrD4MBlBcr2NBEB4dH0GCJZySSLfKsqalp165dsbGxHh4era2ttlh8d370YHGTdYhWaZnEvohnJJLp7E26VlZW6urqCgoKGhoaqCQtXlM3FJMlVAxy25eF8Wx9fT0tLc3Z2dnFxWViYoIfX1tbu3LlipOT0/Xr1/FvSUkJAuzZs6elpUVizKurq/Hx8X5+fmz/yJEjiCEgIGB0dJSH6ejo2L9//969e8+fP49/z549iyu6ubnpHD4jEl9fXwy0jx07hn/z8vJcXV3d3d0rKytFITMyMnBd7Ny6dQsx43ISP+dYWlqK4Tx6wMHBQSQbeU9KShIGOHHiBFKLi+ISU1NTERERjo6OoaGhKDqdJYOokGtkobOzE4lH+SP91dXVPEx+fj5i9vHxQZyoICQeucApWhbmMSHBOMvT0xNpCw8P7+rqOnDgwL59++Li4oTBcnJycBBh0tPTx8fHg4ODkYCQkBAtz3vU1NQ4ODggDTdv3sS/KHmk7fDhw5OTkzzM9PQ0HCAvLy92MDMzE2GQkebm5pmZGZQ//kVd6ywi6fZGIpGMJYvn2dLS0oULF+bn58Gb48eP8+O9vb1nzpxBf1dUVKRQdn/o1tHzohMEAqXE3NjYiM4dyFEouYWOeGRkBFTAcR4GmEQv2dbWhmjRq2ZlZaFDBCd0Imd4eLiiomJxcdHe3n5sbKysrGx2dhYZEWZBoeyCATD0oehAb9++jc4d+dq9e3d/f7/2+JFU9NRvv/02zrp37x5wMjAwALxhn4fx9/dn6wugnp4eEAhdNi6HHe2R19bWgjesx79//z5KFVkICwsDznkYVsjIIFAKssKrAPkwtsC/2iNfV0qhfMo+KioKZYsCR8J27tyJWuDBUC937twB/lE4OH7t2jUcRHUXFhaqjXZhYQG/ojzLy8uB4fb29qtXrw4NDdnZ2d29e5cHQ4SHDh1C5MgdLo3IUW4AGBKDOqpVCsUI/BvL3kgkkrFkDfON6I8iIyMxdlb1vTC0ZzxjAtXQiUvkGYSBPOOZQrm6DL4aLqS6rqyhoQH9O9sHeNALCy+qVnNzc6mpqfADECGLAe4CoCh8PQpQDYcD7oK3tze6Y3YQHTc6XJ1PnZ87dw6OC7wWUBPnwgMLCgoSJR6FA7/q5MmTfP4KV0QxoqPXHjmGDujoo6OjmcNXX18P3w55QdcvCgk8wLkBjdi/8JhBWSklj8EBco0KBTmQF8ASlxPmGgdRHQcPHhTSFwUIcmsqcKS5qakJziXyiNEDBiiBgYFIOQZDwpAIA1cPnEa7QmtZXl6GcwaXkfEb4wMUGs/Rxu2NRCIZS9bAM3Q9GKEfPXo0JiYGHTc6NfTR7Cchz+DcsIkj6TELeQaPCn0ZekD0d+gE0SfiWgyNQAV3dJASFxcXDPy1x4xeFS4RPACAsK6uDr1td3c3/DPEDC8HF8UOcgEg3bhxA44F/C2chZ4X1wUVtEcObwl9LpCAHh/+Cnpk+HNVVVUgRHFxMZuaw0VRbvD24HngX5YRIBbkQNq0xw+ewQfFuTgRxQs2ADwofxAiOzsbHh7AiciBH/CGlz9giZ808Uaky5cvgyU4BZGgoIAWJD4zMxMRosRA/ZSUFPhJe/fuRaWzxCcnJwOWmmYCcRypgnsNMuHEvr6+0dFRVCh8NTQJ5Aglxhw1Ic9QVigN5A4XnZiYQDWhATBf0Fj2RiKRjCWL5xm6G4BKoZz6Q1+vUN425z0y+kT0jNhB/wW3Bp24XpFXV1fD7cAO+ASeKZSTYMePH19RCt0o/iYkJKBvZV0qel4gpL29XWfMoBe724f44eUwzwbdNDpcXIjFBl6i+wbbXn31VUAOMEN/nZeXpzNyxl3k9+2330Z/DYSgI4Znhq6c+V5INu/34V3BccERkA8+ok6YKZTfQ2AjBsAPzujg4KBC+fYKYACQQOJZJK2trQAYSh77YB4IDZpKKXZ2pwogVyjnjeGiIfEYpvDTEbODgwM4DdLY2dmBPbm5uYhfyvtl7t27h/EHYM9eGYW8sFt6vEyAN5Q5fq2trQUvcfXy8nKUPHaQWYk3L6XbG4lEMpYsnmcLCwvwutitMrb0g4l5HujQ0cliH/37tm3bEhMTgR8p843o2tCfAgCvv/46uAL3Cz0sekx00OxTAEzAzAsvvIDjYFJZWRk62Z07d8bGxsJN4TOEagUfC1HBt4DbgQ40JCQEkYBeSKGIKOh/0ZVPT0+Doy+++OLp06fj4uJUZ/bUCnAFkoEBZB8uCOguXDKDfCEByBdIBrcSkaPXBqiEyzrUCh09vBmUOWAMtw/IxInMYRW6R7giUqtQoiI8PPzll18GD1BiOhOPekSxsGnAnJwc7MO1gqvNV+JMTk7CYUJsyCCKDg4TagG+FLKD9KiNE6WalpaGACjMxsZGNm2LFCJauLM8WGVlJWiHSgfnwGCUW0BAABxuVDqc1+eff55lCo61sezNZAL+z58/D8caQyKRCZSWlqLu2D6aOloaMiuahtUuVA0si5kGRhVoRagy0bcMMZpE6aGFYzDBbAfjJ1SElMU1nZ2dqBEknt1DxSAV5547d06UEfyLaCsqKhTKyRWER2WhHqVkAcnAaA+GjOba39/PBm3Ce6todcnJySeUwhgOY0T0MNhH6UmJH+HT09ORbPxlWUBpoHnjOA+TlZWFwsd1kWykAQWIMMiR0Gw1CcNWnAujQMnDhDG2jo6Oxj4b7vM8oudBmpE7DLtHRkaQhaNHj+o0eV7gKEwM9WD7iFnY3/IuhY+YWV4yMzMVyjkPJAwXlfs5E2uYb4QHAFNBSQkbN8b46LYwfgcP2MQasIFgwgURWoSo0J5YDBBwAovC6TgovArcLHRtDQ0NCIlLwNgQGMHQVrQ7OktLS6hjhGRuH/5iHylUpSCO4KIIjwaKPMKdwrUkmiizOnRM7FrClZkQUo6D+AmND2EQOWKGj8iSpN3yURowNpAJpYGrsCwjkaJ6YfecED/Cs8Sj/HUmHoDhaUD6kUKcKKQO60BxECWPykX/iMgRM5KhaaYX6UQYBECVsT4XNYUsiDKLHKEQEBIXVShv4+EU9Ag4HT+xIsIR4ZJIS+EZYINeEsDesWOH0JHFCACDAwxQWHuGz41OHI5pQUGBdJhhQLNr1y62yhcdGaCIfYzY+C1P9MjoAeHpYvSJPg6wwbAMAym412wuXbsAEpQ8ukuMP1ARGDKiojHOEC3/wRgUw1Z0ndhHZ4rsYNTCblHrFFoCxqMoHCQVKUT2ARIMMYXGjtSiYaA9oKkDDIAB/mIIK2SGJiEwUoLEI78wPXTuKAREyD79yIQ+BD8hzu3btzMGIEcYkTMq6LQadCBooigWjKdRVvg3JSUFJcare2pqavfu3eAQRs9IzBWlwGNHR0ctS8xQ8mzVFc5CyRcVFQHJbG2dMBjYjFaEkatCeZsfjQo9AIa5YCHyXlJSgixjdKjXOMkWeUYiWYo21z8DvwEGuOmi9UQAGFvQxMdq4BObqJcitiQVHRl7awl6T/TR6IsxiucRYof5YcAMejd2EBgAOHUu1lUo1+uCxzgRHjZYgp4aMIDjLryDwPxp4Bn9pkI56lIo1w2xl6roFPp3hESc6PQxXoG7g0LA6TwAeAZ0offHRTHKZFnDSBedOJtU1yKMbhEMiWeeE45gOAUY+/r6gmGiwAADm/lnWWD31CXWBWCMYQSSCryhxFAFGDfwsTWKCLWfn58PF5CPV5AeJycn4eJhkTA6QbFgB6cA8BhBIheIAX6eqBkgZnh72EdjQGYVyvl8uIksAKomKChINOqV276IZySS6ezNZGK3SNFrh4aGokdOSkpCX8OW58Ap5wt0FUq8sfVEesWP3p/xDB0W/Ing4GD8Cy8KHR8G9aCpQjltiJjxl52CNCA9Um7ZotOH24eeHb0zeAkvE5H7+fnB4UNvi0tcunQpMTERfgncGt6BgoLIl5QlSAAwYIZuGv4EEIUT4d8gC+AZemF0zUjqvXv34M3guI+PD5szVCi9LilLdlH4IDf6+tTUVJQALgEeI1r4KygiZA1sYMuMZ2ZmcJA/FAR3Df4WQ6AUAWCMKDgFtXDkyBGkHFmAa56QkAAUgTRvvPHGu+++y2YgFMqJX7YmQFOcg4ODSDxiQMYBNjSMCxcuINdoPwyZqF82kch5hr9sKICrs2eQ2Lpi6YMkY9kX8YxEMp29mUx80gndJbo2NvvKpmfr6+s5zzCuRwDhTWKJQteJzppfaH5+HqP+0dFRXIX11IgZBOIP1YANOIVxTqeYp9Le3m5vb8/WH0HIBdwF+EaIHwx2d3d3dXWFd/L2228Db2AGyC1xCRKIuGPHDpz7yiuvAC0MsfB1HBwcrl69iq4fMOMPaeTl5cGvgjsCJiEBUiafQQv05uzmLnjGEYvuHmwArTGkYDPqKHkkg90wA1bZs5ISqwCljTJnziIrMZQ2SozdEEEucCFUAaqGPbmkUBIIpaRzIRXaCZKBkoHjyAIjR7gWTsclED8rhKKiIu6fMS8Zbjpz1DDaAPulPytlLPsinpFIprM3k6mgoAD8AF3Q6bMVE0zoBNGrbt++HV1ed3c3unX4Jehepd+6n52dRbRwI9C5gyLo8tBfAzbgIve9cBwBgBz8hJ4RMHv55ZfT0tLQfet8uEWh5A1OSU5ORv/e1dUVFBSEK3p4eMAhYwHYqloIESKbOOKuVG1tLWitM36WTnhpABgKAX0x0nbt2jWUFccnumw4cCgZZBCuD+D0hz/8AcFwREoWAAP09exJ0OvXr8N9uXHjBiAneuR037597JFK+FLwiry8vJCq5uZmKR86BqVQJmyIgMuBxPC9UGJ8yQmiYlOm8JnYgo6tW7cimziu5RUB+AnEKikpQYWCiEg5vGT2IKaQtagXONAoMfjfyAKojJJHBuFMw4HDIAP5RXUI17+YwL6IZySS6ezNZEJfCR4AM0KYKZQLaDFwxk/oDdH1oMPFPkbTOh9z5IJjwc9iS2kSlRLOWKJPTE9PRxhcCz4TetKUlBT0jEgPn/jSItALESJ8f38/PI/c3FycqPZFNsAzW62H7LAkwQGSmBGci7SxRx6RTsBAeFcJXTlLP/wzIBy9M8sCm4rUGTn4dP78eRYn0JiVlXXmzBnR++2AosLCQkZHhAEs2RXhbmpfL80EfnA6YgdFhCtyHiuUTtXly5dRJoiWLX1C+pEkhBQGEwkhkVOklmUT1c3qV/Qe0fLychzEFTFyQvmgdthbdTCUQYnhiigotAEpazWNaF/EMxLJdPZGIpHksy/iGYlkOnsjkUjy2RfxjEQynb2RSCT57It4ZqbiT/BMTU0lJSVNT0+bQ6p6enpSUlIkPt9NIoMikUxpX8QzcxRbecXeU9zb28vfUCxdubm5/DlWofLy8thbqQxTbW2tu7u7we/LIHsjkUjy2RfxzOzU2tq6c+dO9mWAixcv3rx509PTc2hoqLq6+sKFCzjCVmE1NTXh30uXLs3MzNTX1wNgxcXFfME0vCj2PP+tW7fYU6iIFk5eUFCQo6NjaWnpwsJCY2MjYsBZ8Lfm5uYqKiouX76Mn3BFHFlZWcEOwuASCIbjiLyhoYF/S4VkgL2RSCT57It4ZnaKjIxkn7Fmgmfm5uYGntXV1RUVFaWmpoIoS0tL+Atn69q1a+Pj487OzufPn79x4wZ/2WtaWhp7r937778fGhqKOOHtgXwhISEIXFlZCToeOHAArDpy5Mi5c+c6OztffvnlhIQEXAI0BcYQLXvdXFlZ2ZUrV7y8vLBz79494tlG7I1EIslnX8Qzs1N4eDhDERPjGRACtHgr5eTkNDExERYWxt4GBAE20dHRwhcQc57t27ePvfjc3d0dfzMzMyMiIhTKd2O/9tprAQEB+/fvP3ToELw3V1dXUHN9fR0xw1FDAPaZGMD14MGD4GJOTg44RzzbiL2RSCT57It4ZnYCS9gnYxTKuUcgBLhin/66detWR0cHfmXoamtre/vtt9lD+4DWu+++y5/G5zwDpdjUJXvFEY6zF7ZmZWXhCJ+fhH+Gf9nr5+HnwYfbs2cP4kcw9l5tUDA7O5t4tkF7I5lAY2NjsBRZ34QrXewt+FQpprEv4pnZCR4SHCa4TcePHw8MDARCwCSQJiEhAT7W7t278behoQH/wpFi75thr7X28PDgrxVITk5mLwZ1cXFhz/mzz59evXoV2Dt//jxsDOGPHDly9OhRHAQU2VUUyo+2gG24kEL5FRhHR0f4Z6+//npeXh579R/xzGB7I8mkgoKCQ0qhtd+5cwfNXt83U2RmZpaXl4sOLi8vX7hwgb9S2QBhWBkbG0sVZBr7Ip6Zo+bn52FCcI/Gx8fhQo2MjKytreEgnLOuri4cnJ2dxQ4CgEArKys4jn3hGki4d4w6OMgGqsylwz4Q1dPTg7MQDzDGToTdIgB31/ATn70cHBxEsP7+fvbZawx+pXySkUQGZTIBRXv27EGLvXHjBsZ27IM44BmaLpo6/qJhY5iIpgur4XbR3d3NPrDOIvHx8Tl79ixCIgA7C+0cwTDOw0huamoK/w4NDSEG9q3zmZkZRIiQ+Mtehwjjwrk4jphxnAUDzBITE6mOTGNfxDMSyXT2RjK6QKADBw6wDyUzwT/z8vJiUxrAm4ODQ3FxcVNTk7OzMxw4OGFgFfaPHj2am5vL3/wbEBAALpaUlNjZ2eGnvXv3Xr9+vbKy8p133kFs8P/w7xGlIiIiAK2YmJj33nsvMDAwJycHCVAoVyMfPHiwubkZPllISIi7uzvSEB8fTzwzmX0Rz0gk09kbyegCnEAs4QfNwTPmnzF3bffu3dHR0RUVFTt37mSfbgH8duzYwdZJcTGeXblyxcXFBf9mZ2cDfvPz86GhoTU1NYuLi3DUfH19EdUbb7xRVlZ25swZ9mp/sA0JAC/BufT0dPhqKSkphw8fBgjv3bvHXuZL1WQa+yKekUimszeSHPL392cfF1Uo5+rBM29v766url27dt2+fTsyMpLdSwbh/Pz8AKHZ2dmBgQG4VsHBwQjPTuT+GXYUyk+FgWdgFYKBZzgFLh38ufHxcbATTuHJkyfZKwuwHx4eDpcOF4W3l5aWhlPq6+udnJyIZya2L+IZiWQ6eyPJofLycnt7e7hWxcXFMTExYNi+ffvAMxwEgcAVeE4jIyPXrl07e/Ys+5oa3LWoqKiwsDC+DNLLyys1NfXSpUtsJXBOTg7gt7y8jHOBrsbGxqSkJBALwINzBicMjGQfsVQoP93y/PPPs5XDcNHgxrHnYXBWrFJUR6axL+KZtevxx1GvimeesexcpKc/yIWlNU4yKJOpqqoqS6mhoSG4UDdv3oTjVVlZiSOAXHNzM/AG9ys7O7unp6e1tZUFFn4GrLq6uqOjo7+/HzjEv93d3eyz3X19fTgLB6enpxEVIrlw4QLo2KwUOxc/gXNsGSQSAN8OYYDPycnJFqWogkxjX7bEs69+9YM+8dOfftA/CnXypOITn/jg161brSrXjzzyEc+QTewjp6Lsm78CA4lnJBJJu33ZEs9Yz862J5/82E/MiWGbpbsyanNNPDMPeyORSPLZl+3xDM4Z+8tVWfmBc8Z+smKeWa6IZyQSSZd92R7P0LMzejk7f3B827YH/371q2q6fuwzyOEU+HAgH9PWrYrPfe6DHlb0E/7Fhv6XxYZ9HiHO4l4g3xBAdCKLmZ0IR4pNk+JfoU+Jy+GiHMPCNLOfWOTYYbEJ/TNexWaSC1bCrApwIhcqiA8+cJaIZ/iVJx4nKl81af72RiKR5LMvm+QZ6+7xl4l1i6CaiGe8D+UbQn5YUuKNx6b6E4tcoYsEak/kd/WE8fA0CzfOCX6bULixTIm8HDPMBTZGJo5e0cYEmKlewvwmUYlnNiE2IEbvQdps+7JJnvFuHf4Bv6Wk+PjUHH5iYZjHgL6S+Qqst0UL5p4Ewx5vzZx8OAWRSJ/DFJ3IGMB8HVE8rDfnq1pYdlgW+DpADjDhiSKebW4uWC/AfhKWMGMqG3OwPOJEkX8mdDrxK0O4+S3kIZ7JLtQ+n0TR7qnzQZUqeFhTFA6n9BISQDwzD/uySZ5BzADQjllHyfpQYQDe9Ys2NkuJX2E5QrdDRALOCdbWEVhC5XzsRJGzKLQZtq+6wbZV7zOpzRSTOeRC2AsIj4hO1OlZqq7xMUt7IxlZqrMRwlvjqi1TaMVcHIfCpitdxDOzsS9b5Rlrghjms96cDcqk8AzHuQ8k3LSTgP0qZabOYJ4hHr14Zia5MCLPzG/NC/FMdoFnaJBo+dj49LVaJnHaCefVedPiSCOeWY6IZx/2esLenN8VUxtAtX1zA2CrJ9jMmClJwKZHVJ+iEyabTb4hNgZsVZ5tei5YPKrzjczN4vONrKviK1yYLGQlKvHMpOLjPC08462XL31iTYsf5+dijMtnL9hqKaG58WVlaMzMRxSNzNSuI2Nx8nvV/DjJSPZlqzxTCBYj8PsuogDC59WE6xHULlWQQgJdlSOVBPy+lNoEiJKtiWfmmQu+rEPVP2aBRT2XyHU2e3sjyShm0drnG/kdZbYoid8mF41f8a9q4+SDP7VDOm4dWtaRCSc2re/VDWZgX7b3fhDehtiqCjZNpzaA6Faz0AuBMfCl5KK+npmBAXeeRCeyxIhIwOOBvfH1+vxOOE+2cAzIsql2vb5Z5UJ1CCxMHnLB0Cj8VbQ80vyW7BPPTCfOGNG9MUFlfNAy+b0GfhZrkEKeMaeNLWtSCEZXjIKsWeIs2BoCsJbJR2la1pHxhsr6FuKZse2L3t9IIpnO3kiyiC9Q5I+CqKsM8f1v7PBndRQf55nqo6jCI1pmL7SvI+PT5riulqSSDLUv4tlG9Vb2W7vydk0tTlFRkHTaG8n4kgIzhTpc8XcFaApgRJ7xwPw5V7NckWvp9kU825CKO4r/5MCfbAnY8uPYH1NpkHTaG8nIkggzxcchJHzgjENFGIDNk6vONzI3i883KhQfOXmMZ1rWkSmUd/iECaAlkca2L+KZ4VpeXf7B6R9s8d2y5cCWsIowKhCSTnsjGVmqqzY03egVYobf5RLedhUGUOtm8WUdouVIfKEjk6Z1ZAqFxtfxkIxkX8Qzw5V+L32Lzxbw7Mdnfry0ukQFQtJpbyQjS7RiUAvPhE+aKlReiKMagL1tgK9sBMOEy+txOscYW2bFo9KyjkzTOn6SkeyLeGagPnLOvLfkteVRgZCk2BuJRJLPvohnBoo7Z0/G0U1dklR7I5FI8tkX8cwQCZ2zi60XqUBIEu2NRCLJZ1/EMx2q6K1YXFkUHQy+HvwAZnDOzpBzRtLD3kgkknz2RTzTpoaRhr869FdPnXmqeayZHxyZG3ko5KEtPlv+p+//vNxxmUqJJN3eSCSSfPZFPNOmX6T8YkvAAz/sLwL/IvRG6PLaMg76lfltOfBgjf62XHrCn6SfvZFIJPnsi3imTfmt+V8/8fUtflseLP048GB28WLLxS+EfQH//lnAnwmdNhJJir2RSCT57It4pkOTC5MOBQ4PXgKivGH2x75/vMXrAdvezX2XCoekr72RSCT57It4JknFncVfP6501Ly3gGd/HvjnTWNNVCwkfe2NRCLJZ1/EM6m6v3Df5ZLLn/r/6ZZAcs5IBtobiUSSz76IZ/rpRu+N/4r/r9bxVioKkgH2RiKR5LMv4hmJZDp7I5FI8tkX8YxEMp29kUgk+eyLeEYimc7eSCSSfPalhmd66bOf/ewXZdaPfvSjH8upn/zkJ6/KrD179njIrJMnT8bIqbNnz5bIrLq6uk6ZtbKyQjwjkYhnJBJJhz75yU8Kh2LsoHGHd9/85jd/LLNeeuklWYd327Ztk3t4FxoaGiOzioqKZB3e3bhxQ+7h3eTkpPXzTK8YR0dH5S50ud2CnJwcuZt+UFCQ3AYst4v5wgsvyN2NPvroo3L7+kRcEsmUevjhh+U2Z2PyjEQicS0sLAiHYsygjDu8u3nzptwjPLmHd8ePH5d7eLd9+3a5R3hPP/20rMO7J554Qu7h3ac+9SkrQCbxjEQyhcigSDau3t5e+abuiGckkulEBkUimdK+iGckkunsjUQiyWdfxDMSyXT2RiKR5LMv4hmJZDp7I5FI8tkX8YxEMp29kUgk+eyLeEYimc7eSCSSfPZFPCORTGdvJBJJPvsinpFIprM3Eokkn30Rz0gk09kbiUSSz76skGff+c53WEZeeeUVftDOzg5H8JMoDNcnP/lJHri7uxvhP//5z/OfvvKVr3h5eYku9JnPfIYFOHfuHDuCYGrfyILj/KIsVew4riKMENfFtXD8klKq8bDw/Cd2Fq4uSgbEEv/ss8+qlg8SwFKOaz355JPV1dXsOLs0jwT5FV6F/SoUK0yWZeGF1KaHlT8ux/dFQqZUf8JFcZWjR49ajb1ZnEQ1gpaDukZDFTZatCihsaCWWW1yoQZ5AFQobxiqFqEq9quwcW7Edlh2mD1ame2I+jSkU7UiiGeWJw4VNCNueGiIwnasCh7OM7RRbntaXhTGWh5rqRyT2nnGfmX2yRofLiSMk5kBGqKwZavaJP9JlGWeO25O3N64YDxq+wte+8yQYAYsa7zXUE0MyzVsRpQRfgmhobIUsthYXai1SbU/cWMmnpleamuEVzfsS5Ox8FEIdtSag8gitPNM2Dg3YjuifsCabEdT56M6ECeeWR7PmJnxBqeWZ0IHjoudiBaJdsBwiJaNfWYqXKwt8uGScMSqaiSqF1VrNsxQWVNWhZYIpcKf+BFhy1bLAGZpLA1sZK1qk7yTEsagOmwU9Va8BHgHJzRUYWZV+xRR78l/Qnb4qNMSvTSr4RmvEd6fspbArEDYd+M4a2PcXlgN4i9rIWj5ovGfyAxVJ1dEzW8jtqPa9qzGdkSFyX1iJFuVzdYhG+IZa/TcRZPIM97CVBuf2sbNm69o9kMnz3gM/EREJbQrvXgmtEPuOIoQK6xitebKM84GiciXMAZNxcKTzXjD/uUzsSwGliTewUnnmdDIeSdo0fZmcRLViHBCjFe9yI5ERsTHl6oN0jCebcR21DYw67Ad1cLk8Yt6J6uRDfEM7YANHlkF65xvZK2NBRNNZaiKWSzrYZmLJjpFCs9Esw0MwPxf1TkT1T5FGDk/qMX1VAgmNGAhSLmq1bEAqmM6LbOvQleYlQwiYWbJ5jpYqfKOQHXORJMbLTwovMFpufZmcRLWCFoLd8jQPNTe7FHtRjneUINoGMJ2ZTDPDLYdtQ3MOmxHbeLZQUscCxpmX9bMM3aLmI229OIZDya8xSrsT9lx1uDQdlVnP6TwjNs5O5HFKZy30YtnCg03DrWYJQvJ5/G4rbK/ohi02KSw0FjkKBnW4zA7ZAnjFzKMZ5bYMq31/hmrVk08U6gwCe1BuCZCexcshWcG244m/8YKbEcLz9T6c1Yg2+IZr3420y1lvlHkn4mWDLGDfPgpmvVWvYWrnWcKwbQJj5NDUd/5RoWArJoGmMKQCMOuzg2YT32w46J5FS3TsML0sKJA/KzHYfMkouLSd76RHRTdv7RQe7M4iTpQ1K8qNjT5Z8KVCDjIbkKrTkUawDODbUdT27MC29HCMwtdTmWAfVk5z7iLxsY+OnnGbzUL17mKzIOHEUnY4UrkGZ9tF02YKAzimXbLURVf1ixcBo19PvgVLsHQHjMzY6EdCu8NiLKmL89YJ0j3zzZFWiqLM0B0e0bLEkG0ClabzAo2wjPDbEdLdizddlQLU1MFWY1sjmcKwehe4vpG/nwJX98oeppE0wLlLSoPounkGbcKFqdwPCsHz3A5XIhbGl+cyfod4bnMMRXOvWiPmS+hFg4G2b+ihaYKQ9c3SuxozNzeLE5aKos3aeHMG59a5KfAoLgp8dWPrKlvhGeG2Y7BPDN/29GyvlHLDKpFyxZ5phA8+Czl+TP++IjaWW+1d8v4JXhzlMgzYdq2fHzRv5Tnz1TnQnXapKZ7IaJz+dOp3CtSPVHoMAkf8+Q9i/BmgzBJBjx/pvbhVku0N4uTdp5pMhbhmgjVAHz530Z4ZpjtqDYwnjVLtx21z5+xcblVwsxWeMbGO8JGwCcBuJHofD8I2pPo/SBq3y8gamc8Ev7MjWrCRIbKG6gosJT3g6gmXvSeAlWhcQufcVG9mad6y51Zi6Z3HDCh8+J3FHhHxtMpuvUl/f0gOFH4OgkrsDeLk6YGL6x6dOscLdhBoxLRhZsbe2kF/1WtRYjW4mtp2AbYjmrb4+dauu2I+jSkUPgGE6uUTfCMRDJbeyORSPLZF/GMRDKdvZFIJPnsi3hGIpnO3kgkknz2RTwjkUxnbyQSST77Ip6RSKazNxKJJJ99Ec9IJNPZG4lEks++iGckkunsjUQiyWdfxDMSyXT2RiKR5LOvTeDZ+vr6wMBAS0tLV1cXVQnJpuyNRCLJZ1+bwLM7d+64urpGRUWdP3+eqoRkU/ZmLI2Ojvb09AwPD1Mhk8i+PjpiGvMT6sCBA1lZWVQZJBu0N6OouroaI8JDhw7RiJBE9vWxIyYwP5GcnJz27t3r4uISEhJCVUKyKXvbuNbX1728vIqLi6l4SWRfm88zDw+P2tra6elpZ2fnoaEhtWGWl5cnSSRL0MLCgil5Btnb22NQiBFhTEwMdWok4tlm8szHxyc3NxckA8803QAgnpGIZ2q1trbm6up679693t7evXv3Tk1NqQ22tLQ0bSGaT0xESa0+9pilJJhkLKH1Li4uWjbPYId79uyBKebk5NAQg2TFksmgwLOysjKMBeGijY6Oqg0Dyo5ZiKbPnEFJrXzrW5aSYJKxhNY7Nzdn2TwjkYhnG1Ftba2dnZ2Dg4OVrKtKT0dJKR5/nBoMaYP2RTwjkUxnb8bS4uKilnlO0ykw8AGKtm178Bfbpz/9AZywPfLIR8Gwzw5iwylM/CyQTMizZ575KDCJpI99Ec9I1ivW26J/NBt7s84SZnlkHALS+D5DF8MVOKf4EGyKj/tk7CDbZ5BjJyIqFhuJJM2+iGck6xXxzJQlLNxnWMJfZSl85Kvx48IAIrZxhglBSCJJsC/iGcl6RTwzZQmr8gz7ontjHGNCB04YBjDjk41sI56RJNsX8YxkluIdH78Zw6e2hAsHhN0f7/j4DRg2wOc8Y//yObHNsDdrk06eKTbgn5FIetoX8YxklmL9HevaGIdYn6j2ZoxCcK9F2Ksy2rF9Bjl2omi1ggntzdokhWesmiTePxP6bSSSnvZFPCOZpYTjd+E+7+9EE1n8uLBDFLGNM0wIQtPam7VJCs8UH3ejubgbjR0E4FXJ3WgTetIkSxTxjGQh0s4z7IvujXGMCR04YRjRXRniGYlk4SKekSxEOnm2Ef9s8+yNRCLJZ1/EM5JZSifPFB/OYjHpvH+2GYu/yaBIJFPa1ybwbHV1dWlpaWFhYXl5maqEpF5SeKZQqL/Rwm/AiO7iCN9SQetBSCQLl1nw7NChQ7t37/b29k6nJ0tINmZvJBJJPvvaBJ4FBAQUFBRQZZBs0N6MoqioKHd3d09Pz9zcXCpkEtnXR0dMYH4igWcODg74W1lZSVVC0kNXtjzYLNnejCIPD4/Lly8rlN9Co0ZBslmZBc/m5+fn5uZycnKcnZ01GeTq6uo8yaq1sLAwOjp2t/r27aob1TcrpGyMZxIDY0PMjQ31s7OzsmZkZWXFxDzbv3//gQMHzp8/39PTQ50aiXi2mTxjunv37t69e8Ettb+isxseHh4iWa9mZmaCg4P+9xe+/nc/fO4L3/+1lA0wG8j6U4mBsSHmP//cI3fvVI+OjsqXEfDSxDxrb2+/fft2aGhooOb3aKzLr9WVlaXF+WVd28rUPVTc+o2/W5YQmG2IFlGvrZNsQpbNs7i4uEOHDu3Zs+fq1as0xLBlhYcEfesV/zdTRl9N6JayoVscvfywxMDY3kod+/y3/6urvXWzMiirQdXX1zs5OWn6FcOFHtnU399fUVHxd//41Ue+9sQX/+W72rcf/es3UHG9aZ/QGfKj7dHv/e3ff8Xf339kZKSHZL3q7u6+f/++ZfNsbGxscHAQQ2ZNzhnJVngWGvz1Fz1eiev4/ckGnduOmGJ0iyNFD0kJzLZX47se+uZT3R3WxrPCwsKMjAxvb+9N/D71vfqah7/zs9eSBl463aJ9s4sreTAQufSQzpB8eyWh5/G3j7jvdyYbIellX/Q8NUl/CZ9ZFr5tVk/pxTO72ELiGRN8o5KSkvLy8k1sAuDZ5x//2avx3XJU3B/OtD/+VpiHq4vRkit8hFH4GD7JkkU8IxlDm8ezjoJ/IZ6Zg4hnpE0X8YxkDBnpO5kG8Kwx73HimTnIgnlGshYRz0iKD77NwV/+BDjxfe5m8Q9p6vxOpur77Pm7phQffuZKGJtAevHMNS6ZeGY+MinP+DdleIPk+1xqWyx/8xnbYW1S+LUg1RbLjvDY6IM1ZiziGenD+Rb+inrVz4lxkxYav873/LJeRngJheKjSyjUeHV68cw3IZZ4Zj4yNc9YK+X4QbtS/fSaqMUKfTIhsYTfFFVtsSwqdpy8OvMW8YwkeBW9aF/0DWgmnd9hUfveen5TTYhJ0RdeDOLZrdyniGfmIFPzjL8/mu8Lm5PaFitsmUIyqf2aK2+xmr5QSjI/Ec9IWnnG9oXvoedDY03fyRQeF52olmeCF9sbwLPS7F8Rz8xB5sIztq+2xQq5pYlnqi1WlWeCERjJrEQ8I0ngmXC0y6XTP1PtMozKs5CkcOKZ+ci8eKa2xer0z9S2WOKZ5Yh4RpLAM7W3DXTePxMCTwb/LPL8AeKZ+ci8eKa2xeq8f6a2xRLPLEfEM5IEnikESxmFq8jUfidTOArmq85k8M8YzwqzthLPzEHmxTNNLZZPJ2qab1RtscQzyxHxjGRGMoBnaWnvEc/MQRb2/BnJGmUKntXV1VVWVi4tLWl5cXJbW5ubm9u1a9eoSmxZevHsdLI78cx8RDwjbbpMwbPbt2/v27fP2dk5MzOzu7tb9WsaQN3p06ffeOONTXybKskcpBfPQDIb4dnw8PDY2Jj2MKOjo/n5+Zv4/TN9edaU9xjxjCS3fcky3zg/P3/jxg1Q7aWXXvLx8SkvL19cXOS/Xr9+/fjx4ydPnszIyKAqsWUZwLOUtB1Wz7NLly5hOIgxX3t7u9oAa2trycnJv/nNbwoLCzcra9J55p0Qr++D8MQzkmH2ZXye9ff3p6WlBQcHu7m5xcbGlpSUnDhxYmJigv26vr6O40NDQ/jp/PnzmuYkQcS+vr5e0uZpZGQkJSX13598GtuTT/2H0bf/+M///vsvfuH7bxzUi2eR5w/ox7NvPX3j+tWBgQH5Cmp6etq4PFtaWqqvr4+MjNyzZ4+Tk1Nubu7k5KTwS+5tbW2HDx/28/PbRJ41N9ZJ5JkBL3YBz77zZugBbw/qskmbzDN4ZiEhIRhjLi8vM1ytrq5ybjU3N3t5efn7+7/33nt2dna1tbVqI3nw9VvSpkqh9J/+8ee7nz188xdBV42+PRt+6ys/3fbEKz4SeZaRvs0Qnn3zqY7WZtYIZZKQNEbh2cLCAohVUFDg7u7u4uISEBAQFhY2NTXFAxw6dAh2FBMTAyvTFMni4uKkbEJiKsuvycqzH75/7Bc//a/oE0ejI4/Jsp04ejYpcWho+P79+5OkzRNau1nzrL29vaGhge3fvn27tVX9bE90dHRqaioNMcxZR8IOff0FD1DhpehGiVtj3nfReR1IjNUZ8rWE7seec/jeH7wk8qw0+1eG8czi5huLi4sdHBwwKCwvLx8dHcXYDjaF0SH7tamp6e233z5+/PjOnTsBPE1zkuDZhGwCA+Tm2b/vPP7Zf/7e119w/5dn92rfXt3xAuKvSvyCzpDC7evPu/3v//tPd6tvIy8TpM3T/Py8WfMsOTk5PDycOWTBwcH4V22wvr6+oaEhYobZ88z9lbhO6T0Rui10LujCpMDmW8QzdRoeHu7s7FxaWlIo5x45yZhmZ2cHBgYQwM/PLz4+fm5ublOyJvd847++d/hrP3/3rdSxV+I7tW/+yWcR/72CJ3SGFG5vpYx+/vGftrc0kZlbrkzBs/z8fFdX156eHgwkHR0daVG+5coMeSYlZkvnWVpa2unTp9l+WFhYbm6u2mB5eXl37tzZrKxJXw9iKM/C/+W/33w1QZb4Wdt4+Nv/1dZ8j8zccmUKno2NjUVFRdnb2+/YsePUqVPsTgzJEkU8M7q9SVFqaiowhh14Zj4+PhggmmHbIJ6RNl0mWq8PO+zo6Ghvbxcu0ydZnMyKZ9JjtnSe1dXV7dmzx8/Pz93d3dHRcXJy0gzbBvGMtOkyBc9AssDAwP3798Mm7ezsysvLqdwtVMQzo9ubRA0NDWUotZG75bKKeEbadJmCZ5mZmZ6enjc/FC36sFyZIc8cz1ywep5NT09fvXo1Ozs7LS0tOTm5q6vLDNsG8Yy06TLR82deXl7Dw8NU3JYug3nmGpcsE8/sYgutnmdFRUV2dnZhYWGHlKqrqzPDtmE+PPNPjEb8dRe/TzyzNZmCZ6WlpTt37nRzcwPVPDw8aL7RcmUAz0aKHpJIHX151l/4iI3w7OLFi0eOHNHymLY5yHx4ZsCH8Yhn1iETrQeZnZ0dGhpiD9CQLFdmxTPpMVs6zzAifPnll6OiotgttI6ODjNsG8Qz0qbLFDwDyYKDg+GZdXd3wzI38REZ0gZlhjx749RNq+dZf39/VVXV9evXr169eu3atcHBQTNsG8Qz0qbLFDzLzc319vbes2dPa2treHi4pveDkMxfZsgzffssS+TZ+vp6RUUF7GhmZmZhYcE8H3rRl2flOT8lnpHkti/j8+zChQsHDhxwcnLCANPHxwd/RQEmJiYw8CwrKzPbtcgkJrPi2ULx/7IRnsFkdu3atWPHjvb29sOHD8OgzLBt6MszvXhDPCMZZl/G59n4+HhgYOC2bdscHBz8/f1V76KdPn06KioKPhy5bmYus+IZorURnqWkpABjrq6uXV1dVsCziHNBxDOSaexLlvUgw8PDGFq2tbWNjo6qLtNiH60+e/ZseHg4VYk5y9x4Nlf8Z7bAs4qKCicnp+3bt4eGhu7evZt/O5ArPz/fxcVl7969AwMDm5U16TwzgDfEM5Jh9mV8npWXl+/7UF5eXvX19aIADQ0NcOBgkJWVlVQl5iyDefZqdLUcPEPktsAz6OrVqzFKVVVViX5aX1/Pzs6enp5OTEw8ePDgZmWNeEbadJmCZ11dXQUFBZcuXcrIyNizZ091dbXaYICZo6OjprcVLy4ujoyMDJM2T3Nzc34+nt940UMvnkmfFdSLZ2+cumkYzz7/2H+88YcXHR3sHOx3yrHZ73r/2PETxuVZb2/vlStXripVWlo6OjoqCtDS0hIVFeXu7q7JuEygpoZa4hnJ+nkmVEBAgOrbwePj4+fn58E8OHCaHhoF5+ZImyrUwqGD/vr6ZzLxzC620GCefXOr1w93Rv9ge5Qc23e3Hf/y1x4zLs+Ki4vt7e0dHBy2b9++Y8cO1SdepqamGhoaTp48GR0drSmShYWFyfFRubaxkcrrV6yAZ82N9fQl+s3VRt4bYKL3XXl6enp7e2P8CP+sra1NFOD8+fO+StGrHc1cBsw3ysqz/sJH9ObZt57+VWARLvGH2FY5tq2nmh597Anj8owLwz4vL6+bN28KD66vr/f392OnpqYG9qXp3J/94pd/+5XvPfToD+TYHn70h3/9D9945Ae/smieff7bPykrLR4YGOglbZJ6enru379v1jyDsZWXl4Nq+Nvd3U1UMII+/WnF448rHnkENfRgCwz8aD89/YMw27Z9cETTQZzFj/DjiMdyeGbAO2fBs1/4XnzpVJNeJ0rfnj9Ra3Sewc7Zk9RXrlwBscrKyoS/Yjzr4+MTHx/v6uqqZenj93/0r88du/uHuE6wwejbqwk9P/e58MXvPWPp/hl9n9qiZQqetbe3wwNLTExMUurUqVN5eXkLCwtU+hviGYMQQMXhxPbBOQj/sgAQQx07yHGFI4iE84wdf+aZjzhn3jxzPHPBdnjGHtw8cOCAp6dnQkLCysqKKACGiXDa4J9pieQH/+/ffh1W8fvoRjly/fLp5p+6p1kBz+j+GfFMh+CZvfXWW/7+/l5eXm+++aabm1tsbOxGnErSAxQxGon2OZlANV5xainFiKgQ+GeiffPmmcHfBLFEnk1PT/MJmaGhoeHhYZjP+vq6XpEQz4hnxDMj8OzixYuhoaHM/IKCgkSzJSQj84zt8+lH0ewiwxjf1PIM/DMqz1ZL/odMPDPgmyCWyLPKykp7e/tdu3bt3LkTOzt27IiIiJiZmSGeEc9IpuZZUVGRo6Njfn5+Xl7e7t27i4uLqdxl55nQP+MSOmpa/DNj80ziKkQDeGbIPX8L5FlJSYmLi0tNTQ3Ggg4ODjk5OS0tLcvLy8QztVts8n7EX5i1lXhGPJNlvX5mZubBgwf9/f1TUlI0PWFGMibP1M4cMsilp390101mnum1ql4vnrFvNtoIz1JTU8PCwlZWVhYWFvz8/AwbEdoOz9LS3kP8+Es8I57JwrOurq6Ghob5+fmJiYmpqSkqd9l5pvjQGxNOLbIAfB2jJfPM8DXZFsizxsbGvXv3+vj4uLu7Y8ew758Rz6TyDKaBjQ3+mGnwfX4Tmo8IhaNGtghLeJAFEy4qJlk6z9ra2lxcXOzt7dvb25OSkoqKiqjcLVTEs03hmUI5IqyoqLhx44bBT7yYG8+yM940X57xUZ0QTsKnWfhCYj6HD3QJh5isloUTIYx2mgeLJMvgWXp6+sGDB4E0gC0iIiItLY3KnXhmFJ5lpG+zBZ6trKxkZWXFxcXdv3+/pqYG40Ir4JlevNkEnjEJ9/lECPO3mK+mllLsLD6xz8gn3CdZLs+Ki4vd3Nzs7Oyys7NdXV3p+9TEM2PxzIA+yxJ5BgtycHCABYFk4eHhubm5xLPN4RnbF83kc56JFhWr5ZnW9xWQLIBn8/PzZ86c2bt3r7Ozc2xsLK0HIZ5tnGcpaTtsh2epqamhoaEYC/b09GBH9Q2olsWz+BQny+aZ0D/jEt6H1uKfEc8snWcVFRVpaWlzc3MAm9p3TS4vL/f19Q0MDBDqrJJnXQVfNjrPDO6zLJFnNTU1GAu+8847vr6+jo6Oqt8/syyeGVB35sUztTOHwodhyD+zYp4VFhZ6eXl1dXUNDg729/fPzs6KApw9exYBdu/efenSJaoS6+OZxLd4GMCz08nutsCz+/fv5+bmxilVW1trWN0Rz4zGM8XHlzKqvqyA/DMr5llpaembb76JAaabm5urq+v169dFAWCiS0tLly9fRpiNfCyAZG480+utVAbwLPL8AVvgWU5OzpkzZ7QEaGtrS0hISEpK0vKQNfFMKs9IFit5eba+vg5QTU9PM89sUClV/4wpMTHxyJEjVCXmLPPh2aWs522HZ8XFxdu3b8/Ozi5Uqre3V2RlR48evXjxYlBQ0MmTJzVFQjwjnlm95OXZ3NwcENXX11dQUKB9nuTatWsHDhyYnJzUFAADzyk5BegWFRWdTYg9l3hGpi01JVm+yLGdPxufknz+XKIhWZi7/JfoArSHyUw7/8rW3377ZR9z4Flp9q9sh2dVVVWBgYEHP5TqR6gXFxfxNz8/39vbm3hGPCOeycKzmZkZFxeXzs7O0NBQjB81BausrPT394frpiUq+Hnj8mrs4b//8j89s/PLP5dl++dntv/pX/7fr/zCTqb4v/JLuy/+v+f/4vNf+eqv9xhwel/2n6ML0B4GMX/mn773g9f9zIdnwUnHrJtnKysr9+7dA64mJia0f2IJAzI/P7/Lly8TzzbCs8E++kAj8UyDZmdn7e3tY2Nj9+zZExISkpGRkZqaqvp9ah8fn/fffx/WiLGnvl/BMJbW11b/8RtPvJLQg2Ytx/aH2La/+efHX0vslSn+18/2P+OV/aUf/eat1DEDTh+99DC6AO1h3koZffzFfd972dN8eIb4rZtnoJSnp2dPT8+pU6e0fJhieXk5OjoaxqUlKuKZzrbxd9/96VNP/vsvfv5zGTfIkuN/9jfPXS8vHx4e7pNNG3khorw8g1MVGRkJUAUoBScM+6rPU68ptazUZoEdPPvS17+7NfqeTN3ciydq/vofvy1fN/ry6Zaf7D//99//pRSDV91Gih7S+ZUyGPxjz+0xE57dyn3KRnjm7Ozc0tISFBR08eLFBaVUv+d5/PhxLy8vjBRFt9aIZ/rx7Ds/+dGOyJ/6Ff3EJ1912xt+ENHWZH1d7a+6N9+Cp1yS//dDX/lZQImBMWjdkOwfvHfsL//piZ8fvCpH/Nh+HnTtr7/zi9ycDLTAZdm0kae2TPQ+YvMX8Uw+npXl/NzoPAMjbYFns7Oz77///r59+15//fXdu3cDWnDXVEeE8fHxx44dO3LkiJZlkMQzKTz7uc+FP8S2oXmobgeS4pSDs++q/VX3drr5d+EVn/vq91+J7zIwBq0bkv2MdzZczNcSe+WIH9trSX3/8PRrhXk5ZtuNE8+IZx/xzC620Lg80+urLgbwzDUu2bp5hrFqVVXV5cuXr1y5UlJSUqyU9jvNxLPCrK2IPzZ5vwE8e8YrG3nZ+GSDmi268bdh5Z/7yhPIi0xV8DPPzL97/L+REZnaNgr/H556lXhGPLNRnun1FnwDeKY9wVbAMyPKdnhm8NpX4hnxjHhGPNsEnnUU/AvxzKJ5ppf/RDwjnhHPiGdWyzMpCSaemTPP9OKNOfDs8NlQAz65RzwjnhHPiGeSEvze6VLiGfHMNDwz7BOyxDPiGfGMeCYpwXobJPGMeEY8I54Rz6ybZ1JuRxnMs8KsrUbn2f3LnyWeWSjPLmS+RjwjnhHPiGdy8UzKckGDeSZxJZtePEO0xDML5ZkBvCGeEc+IZ8SzTebZyfNexDPiGfGMeEY8I55ZPM/0etJIX56NFD1EPCOeEc+IZ+bFs6GhoeDgYF9f3428iZJ4tnGeaX99FPGMeEY8I54Rz3To+vXr4eHhPj4+ExMTxDPimU6ewY8knokE2xkdHdXyeQriGfGMeGai4WRNTY2HhwfxjHhGPDNAt27dcnBwcHd3n5ubI54Rz4hn5s4zx71Oj3z5G1/+5vdk2v7pa9/+Pw99CVQgnlkKz5ryHiOeMdXX1yclJfn7+8/OzhLPZOWZvq/ttz6eXS68SDzTodraWm9v78nJSU0BfvXLX/6n18Wt0U0vRjXIsb1wovav/vEx+bo5W+bZ6WR3OXhmwJv0rHi+ES6aj48P8Uw+np1LtSeefenp1xJjT3Z3tHV3yrWNjo5aNs+KiooAs9dffz0yMlILz37iLWM3tDWy9q+JZ/LwTGLPIp1n3gnxxDORKioqiGey8sywz6pZGc++9sy2v3zk6w9/6+mHvvGkHNv//cZTX/vWdyybZyMjI93d3f39/Vq+rks8s0SeZaRvk4NnBr/p3Ip5VlVVBZ4tLCwQz+oufh/x+ydGE8+MzrOv/tfrT9qffOPcIK4ix/ZyXPc/feN7CsW6Zc836hTxTFaeVef+mxw806vn0pdn5Tk/JZ4xJSUlOTo6btu2LSIiwlJ4Fpx0TCaeGfztcuKZFJ792/aIP8S2ydVPRjX+M/GMeLZBnrEuxrJ4ZsBKM2vl2crKyvLy8urqKv5aCs/04g3xjHhGPCOeWSfPDP4SFT1PTTwjnhHPiGc2wbNj5wIsgmcGPwlEPCOeEc+IZ8Qzm+CZdvAYzDPtmDSYZ3mZfyCeEc+IZ8Qz4hnxzHQ8k9iz6MszA3oW4pk58Kw856eWy7OUtB3EM+IZ8Yx4ZjSexac4Ec8sl2cG8MZ8eKbvY23EM+IZ8cxKeFaW83M5eGbwzA/xjHhGPCOeEc+IZ4bwTK+eRV+eJaXsIZ4Rz0zGs5Ls54hnxDPiGfFMFp4Z0LMQz4hnBvPMsNdoEc9sjmcLCwspKSnJyckdHR3EM+KZTp5dyHyNeEY8I54Rz8yRZ2fOnAkNDY2NjfX19dX0QULimaw8kzKXYj48M7hnIZ4Rz4hnxDN5tXfv3tbWVux4eHhMT08Tz0zPMykzeAbzbF9cmhw8k/hYmy3wbHZ2NlIpZkfEM+IZ8WzTeObp6cncMm9v75s3b2ri2ZMeF38X1fTbEw1ybM8dq/3slx6TL/7fHK357Je+LV/8z59secr5/Bef+OXW2G4DTk9OfcCzcyk7tIR5Mbbr67/Z8+2XPF+M6ZQYbf3FBz3Le6cKpQR+EP+zDt95yevFmA7tIUuyHvQsnnGx+mYTl3jom09jYCRfRfz6aO2/mJxnYWFhsbGxZ8+e9ff3J54Rz4hnm8kzFxeXnp4e7Li7u4+NjakNExAYEHehLOdGS3Z5kyzb9XunziRl32iWKf4smePPudGceqkq9lz6hco2A05vvrYdtoq/2i5R0ZqYWXg2pxg7EqMdu/pdRHvp+mVJWZAcf+/VXyDa62VxepdSRWtMYkp6SbV8FZFZ1uiw19mUPFtbW3N0dBwcHGQWpOkTaLbDs6a8xxC/d0I88Yx4tgk88/X1jY6OzsnJCQgI0HT/bHllZX1tRbG+KuOGQrTo+NfXDL9Epzts9cFfnZd4sEmO9s4PH0Q736ZHFqTEf/fB120UE5fNsha0veReDoNaXV319vZm+25ubvX19WqDfff7P3zm0I3fRTb+7kSD0bcXTjY/vS/lc9/8z9+f6dYZuEHpte+NSZMe/4sx7U+8Ffqlp175fZzu+EeKHkL8758q1CsLvz/T9Tdfe/I/3TKRF7UB2KzAkaQAA0spsvGXh65/+u+/hbzIVAX/4Zr+N19/ChmRI/4HRRTX/Q///vL33zn84uk2mS7x3PHGv//qty2bZ62trSdOnDh69Oj4+LiCtCnq9FDyzMPI0VZ88UG0C51Gjvbujx9EO1liccUsn3/W39+PfVdX1/n5ebXBDvj5XyyrvXSr+dJN42+Xb7UUXL+bcaGg+HabzsAT1x547WVVxXrEf7v14pXKrPyS4mrd8S+UPqRv/NiQ8vSc/ILrNciL2gADZc8i2tsV8QaW0q3mosrGtKwLyIt8VZB+IV9KFRi2ofCz8osvXqmSKQtsc3X3NKJ9menzZyTimZhnRo/WMnmmUN6Bjo6OjouLw6BQUxjlzId82xrHq+7AH1Rfh1zxf9DqOoychaZXlaOo4o0VlLQsyF0F5nuJdU1TdMQzEvHMJnjW0tISo9TS0pIFlILc1SdTq/uAZyXUW1iQfRHPbFKWxTOZot0Me7NFWSjPLHaW23ZEPCMpJSvP1ldkiZZ4ZqEinpFMZV/EM5uUrDwzumTC5GbYmy3qzo+IZyTT2Jfl8WxoaOjKlSvl5eWi5ZGLi4sVFRXsgbapqanr169fvXq1r69Pr8h7e3tv3bq1sLCA/Z6enkuXLt2+fZv9y1VVVVVcXNzZ+cB+JicnsY/EzMzMSIm/tbUVcbKnyGdnZ2/cuHH58mVcVBRsYmICceK6Kysrd+7cwSlNTU0Ss4ByQJrb29uxj79IHnI0NzfHA4yMjPRcfR222nvtDfw7ODjIyhMXlRI/slxWVoYksYcIUc44/YNyVvYsSACOlJSUoPxramqWlpbu3r2LbCLvOu/9Li8vs8AsSSjVrq6uhSufQ7Srq6vCPLJg1dXVKCXkCNm8du2apoexmBADSgZn3bt3D/8ODw+XlpYi/aKHIFlDGh0dxT7KrbKyEqew6m5ra2PlqWlVoU57s0XJ7V4Tz2xVFs8z9HfR0dExMTGenp5paWnCnxISEt588030odjPysoKDw8PDQ319fXV3scJBXK4uLjY2dkBmTjr6NGjZ86ccXBwQEf5USO/e/fgwYPHjx9HSHR5iYmJUVFR+/btS0pK0hk/emckqaCgYM+ePbW1teiy4+LiYmNjDxw4AADzYOj0U1NTf/WrX4E0LS0tSEZ6ejpOYV2qTqGDfv3113EW+lwk9dy5czgXWeMBLl686Oayo7TgzNXibJRnZGTk6dOnPTw8Tp06tba2pj1yxHnkyBEUS05ODtKDfj8kJARHfHx8gIEHI/GKLyJMjlJBQUHe3t7IaXBw8MmTJ5GMgYEB7fEDfsBYdnY2avOtt95qaGhARioLD0UGvgj28GDAmJOT09mzZ3fv3g26oAxxCuoaCdPW71VU7N+/Pz8/39nZub6+Hmch415eXikpKcJgqFM0JPAY+4gWuUBLQ3sDzFCeqGhkBJVomL3ZoohnJHlk8TxDhwtvBgNqdHMZGRnCnzCQP3z4MOv14LqxYfvevXsBJ4mRT09PozN1d3dHt4uxfHd3N+JBRwbw8DAsZrgjiBlXZEN7pAQ9nc744WzBpwFCADAM+SeVamxsdHNzQ1J5MIQBI5HBjo4O9O9IFU5BRwzPQOclgFjAgz2xjn+RBeQFsBHy7MKFC4AQMojCxF/miMBl9PPz0+l2ILXozeH2sYeIkWycDl8NlxB5sVBERARIABcHgwMEA/WZYyRFIBlYiOJFUaPckODMzMyPerCKChQ4eI+/2GejASTD1dVVy9PNYWFhwCR2gKjk5GT4Z4gfQxPRwAiFhsEQKh3lgwgxQsIIA3UEwrELYYgAEBpmb+YgNDC0JfidokkF1NSNGzeYK4+aRX7hiKOJ6hU5Wgh/xBtDGVTK8rWHhLxBbTLfnc2vYJRQVFSEkDiuM3K0TySbzw2gbcCOFkv/VpVnaGksGWh4uBy6BYkutUI5SYOrrFX/K6KtL4vA6bB0/ivGbUgtChCXZmbLJmyam5slxl9TU4Ms4Cxh9oXtFsM1PkWBJoceDGEwbnswZNQlRIhzWQnD9icmJlj2hTM0aNhNTU0IxuJHD4PAyILOB4Lr6upwFsb0rLfEWYiZvapGKGSNjVyRKewjs0gV66JZw5NeF1bOM4XSiwoICEDniJJCxwrnic3/oJLQgQpH8eh0Tpw4oVfkKHd0YexhVdg2Bu/gGdoEGiuaF6sVCM0LvT/z/IAc8AOjfp2RI4W5ubn+/v6IFvWNZorOFPFjyI8r4nJoXthB3w1ThEPDL9fa2gqXgqVKuxA/els4LiAi/i0sLMS1kDzEgDhRVvh7+/btQKXASDbHiK4E2ZGSBZjitm3bkAWUEsMAnDO4Snl5eaiCMqXYInKgAgzgDh+yhpRInNJEelDFzAeCMWAfpQQLRCcFEwLqEDmw+tJLLyEXrCPAhVDXyLiWaOEywg1FawEpUUroeXE6GhIMjDckmD2iwmAC1Y1kYHCD4sK5SANSolDOUkoHsxkaFPqv0NBQ+KCoNbjyQpgh16+99hpwjhrEeAj+Oood7VDiUwEoN7j+dnZ27PUlKCKMGxDJRN5fcN5gZIDBH3PoIyMjASS09piYmF27dqFP13kJtC5EGB8fj7YEUB07dgwO9GT+p0U8Qw+L5oFqYp0ARkKoPuRICjIxwoMtvP7664uV33/wFdkTO2GkGIDyAGgADg4OKMCsrCxYMZIN+0IWdu/eLeXuBuiC+JEkNDBQmX1pBBEK3/OCbCIAsvn222/jOBKAXNjb27M5A+1CeJQwTn/vvfdglWjnSCfa+ZkzZ/iMPYoOtR8XF4ciglGg1mA46DwxFNZy36SlpQWDeEQO20dnhR2UP6pY1Mfi0u+88w4bfYJeKDp2CtoDMosBJSJBkjby2JlV8YwJo3L0TeivU1NTUW0YLIh4hkEE2pkUBmjiGRMMBhUPiKIm0N8plCNQdOgsDJoImh0ajV5XQQuGK8n2McRzcXEBh9Cw0AjgN6A1gHAwD5g9fsWF0K1gyKYzWrRFwAZtF1lA6+e33FJSUtBSUVaIHCbBR4KIFtfFDkiGpqbpWwcinqFU0fcBKij/+/fvK5R3+4BGDL5SlGKDLxQL4mRndXZ2ollLnC9llgNLE8IPtYxeElaEokYvjKEMOl9UBLLAjBwBUPvax33ol5Ff2BI6O+7tISpAC+xEDDBsdPewNM4zRjuF8iVtrGmh7tASpPSM5mlQqH0QCz0a2jDKU9iPozxRyB0dHTAl5nmA5ag44dBei1BuAAlGOWiBiAFtA44OGqGQZwrl/W+FcnyD4Q5iZj4BungM/HVeAoExlEEKUS9gCXiAGp+59FkRz2A+qFA2ZcJdKIwIVacQVIVkoD2gXS1UPIFoR3qqEBVwyAMwGCBrzI6QTcYAWLFOJKOIQGK0PZYSJB5ZQEZwLnN6hELtoPARhmUBVJNyU4PXJkwSCEHvgRjQ5nmHo1DyHnlEFoBJGCwzNLQK2IWW2SwgPDw8nJk2GIZIUBQAIUY8wmCAOo7gigrlG+fZqBTDF3QybCoIPSryovPWhk3wDFULuqAmUP1oBMI7+agVDBZYB41uFyM+trJDywSUaiMAt1CpoBp6Z+ZzoOiFo344OhiBYqiOzhHuP1oY2g0aARvXa48ffSXaBE5Es0C3iFEYDACeAUZnfLwP82hTCi2ATXRgOIM2saiU9viRADADKcSYF70VbBiXQ8LS09Nh27wLRqaYESLlKEZEjgSgNSOkcM2FWiG1jo6O6KSSlAIDUAV1dXVIpPAWIKyUfxWI2QkaMdIvpUNRKCcGmZHgFFQ3cxeQKR4A/6JecEV0nUj/hQsX0MHBWpAFLeM+xIMMoqgBJ5QwzBLpRBWgp2OWxhsS8I84cXX0syg9dKMs17B/dDH4F2UoZYBpngYFVLOJh+bmZpQG+k0M6lEyKD20OraSiAnFywxKumAaaHvMFgB+lC3jTd3NHAxE2OwlroWxGu+d0chBCC3fvuGCbwSfAH0xvA2kFhaEqmT+WVfTFWQEhg8Go/2gWaISuV3Af4LF6bRQ1CyyzCZmlm8+eBnp6WPuqHr0zgADRjZsTgg+IgoKWSsqKmInwrkHnnU2CQRATtFW0YrQ16MVYQgFM0TbRmNGLSBHbPoOloJBFQckDBaXY1MFUoSRK0qY9YRow0gbYsY4AFlDJLjuoUOHtm7dCsPno0ZYKMpNy4gQMSDxcCQQDLWAWkOvAjNHc4KN4zj6W9YJoHY4z9iCBgxtMV5nnQ9G21JG5zbBMwj9Fxo0GqtozgeQQONGQ2GuOswVoyoEk74yEEMznI5I0LwATvSYqA82cccFLwd+CWJGSFQVW3KCfQTW9K0ALvSPSCQCs9cUscEvDINVuUhoXkgDjAfVDxtDSjCklZgRuPms9cCMYZm4HDoC/itM6IBSCIM0o90jcvRB8G90ZoGVEkoAGYeFw4xhLfhXVMgY6cPm2bgeYViJoaDU5lRVOJfdjWCziEgqLie0NFgmahbJRppRSgiPfZQSgmnxnNCfIrVsslehnDRmDQmpFQZjs2FsDhlGi2iRABgt6gKlhOP4i4KV4qKZs0HBTJA15BFcQavGsA9DHGScfzUerQgDRIlTxEID4TxTKN3B+wX/B2AoyIqEVbJZDYwVIiMj2UAThEN4vTo4tCuMZXnnzpa/3ipLRUbQpJEptDd0qe+++y6ywGZBYdFsLkG7MD7btm0bbPmdd94ZzP8yc/vQwMASdNDJSqHvZoHRg4MTyAWMC1nQ9OkroZAY9EtsmgdU43e1MXpDt4aiQ7KZKbW0tHBvCS0f/Qab7pYiQAWMFE5gYtgKKgNIGJqj3jGMgz0iwXDa2BIq5AVVr3onTCS0lvPnzyNyWBw7AjtFXaCEz507h5Ef62cwdGA8Q2bZXX+QD+4BAy0yS/fPSCTLkxkaFHAFrx3oAs7RhQldCnRn7IX9cGTRe6I/RceHQZj0qSEExjgMvRh7ZgOdMjo40f0tXJetpYILAn+I39mScpcO7gW6ZvTybMkuOkewba74r4XxI811dXUYuyAMMgv/Eh0uRjBIkk7/CW56Q0MDUrhz587JkkcfrAe5dQHptLe3R5w8GLpjXBadO3gA2qF/R65xUMpUEMgHasIZxVgKQz34fLOzs+x2AA8D/xUxgxzYwdXBVwRgMzRSZgWARgyC2T6KaHp6urS0FGXOkwfG4Oo4DghhvIiSRAY7Ozu11zXqCL+iJDGkQykhecgF6gLnCp84QoIxWMGvqFB4gfDRUVa4OnzNlJQUtA0UssSMGGBfxDMSSS6ZoUGxO77ogtHXcFdDoXwaEj4ueMYcdzipCIOeKywsTLj4VovQ38XFxaGjhOeBjhJ+Brxh7M+X/M0D3qxMsmBwNdDb4lqIGeTAFeEx4yz4DTpdXvS8LDAG++hbMdJH/zhX9L8exL88KgyJvhuJUShdH/AMmYLfJmV9oEI54Yweea38C4g2yOd9dhOI978gMYoOacDfvr4+pATem49SwoXQmgQAIM04nT21CQ8Y5YwRhhAkSCcKh01RYJABdxOn4C8qTsq9TLi/fG0XeIZzkQW+uEyh9IlDQ0MRIVspBhiDN2yuSEtds3vnqFB2qw8uHQoWR8rLy4VwioqKQv0ig2lpacgg+I0EoEWhseESOM6WAkm89aCvfRHPSCS5RAb1QDK9NYYLkcv3VhoLfMuaLdsX8YxEMp292aKIZyRT2RfxjEQynb3ZoohnJFPZF/GMRDKdvdmiiGckU9kX8YxEMp292aIsmmdLg9SMLci+iGckkunszRZl0TwjWZR9Ec8sSRMTE1IeCzWB2IuMJb7Zj+zNpkU8I5nKvohnZq35+fmrV69mZGTgL3tPLnuqRrpmZmbYW7RFx8HFyspKg59qHBsbc3d3l/6+fLI3klwajHmwGV3EMwu0L+KZ+Qo+EAAWHh5eWloaFBR048aN06dPJyYmKpQvghOhiP+7/qHYv93d3du3b29paREFa2pqcnBw4C9sVAWb2kvwI+Pj415eXtLfJUb2Rtp0YUTIPsQhKbTMPFtSiirFuPZFPDNfDQ8P29nZsQf7FxcXl5eXT5w4kZKSUl9f7+fn5+npeejQocnJyZKSkn379rGvsdy+fRv7vr6+/O12vb297A3LsbGxOAtOFdAI5+zYsWMvvfQS+97m5cuX/f399+/fj338FBYWtnfv3pCQkMjISPYK9qioqLKyMlwawdjXAHAt4pkB9kYysTDwqqioQDOGNQ0MDLi6ukr9zkP7HkXTqwrlC7RUvyCPgR1Givq+3FIoDEz1nWsh6bQv4pn5SvShCsWH34zAsK6qqiotLe29994DgcCniIiIhYUFOFsID+YJ3yPHeNbe3g6YMfuBSQNOXV1dAJhC+e5gOHC4VkxMDCJEeEdHR/Y646KiooMHD6IjAN7u3r07NjZ25coV0A4njoyMgIXEM33tjWRKoZFj2AdyYGSG8VlHR4cePPtQ4eHh7AXiQsHJO3z4sMT3a6tVQkKC9s+pkwywL+KZ+aq1tRVoEX40ln1M+dq1a87OztgBqGpqavr7+wE5eE5gW19f36lTp0JDQ1X9Mxy8ePGiQvlG1EuXLnGegW3gWX5+Pg5WVlYODQ15eHiwV87fu3cPCcBP6AswIAUsYdjw1dBHEM8MszeSKQUb4Z/ihJsFjwo8Q8uPjY2FFaAB37p1a2ZmBibj5uaWnJyMEWF0dDSaN/seDTc6DPXQ1NHy2XdeYJh37tx5++23d+/eDdPDOA8/eXl5nTt3DpyDHR06dAhGlJqayr6HDmvCFevr63FRHx+f06dPI3KcSDwzun0Rz8xXi4uLLi4u58+fv3//fkVFxfXr1zHMhNVlZ2cDMM3NzbCo6upqBGOfZ4TxwDjZC0z5J0Zhwzt37oQFwtPCiTgCw4M3Bgra29uDXoCWg4PDjRs3cBWYGfs6Bv/YBAanr732Gvv6JQuG9ABycNrYN2epmvSyN5LJND8/D3gIP5uCNs8+PAsbgUGBOjCKuro6/nXsmzdvYr+9vV145xg8A41AvjfffHNycjI3NxdnTU1NwT8rKirCVTDIg2GWl5fDLoqLi2F67NME09PTdnZ2uGh8fHxYWNjCwgKugtEhho8NDQ0wZOKZ0e2LeGbWgjFEREQEBQVhTAcTwtAPROns7MRBWAjGkjAbGAYsE1YHqmHQB9QdO3aM3/TG4DEuLg7cunDhAvvKVEZGBntDdkpKCgK3tLRUVVUhBuzD8CYmJhAh/3I8fkJs7MNIoCCC4V+ciMTgr76f/yZ7I5lMy8vLR44cQbPnRwYGBsAzjPDQ1Nln7QICAoCo9PR07JeUlCAAnCocBJb4C+A5zzAQBOdggL6+vmAVMHbt2jUcwcAOo8kzSrW1tYFnMEyFcj0XQsLc2OgTpgTgwXyATFCWeCaHfRHPSCTT2RvJlAKWduzYMTc3t7KyAr8KQzcXFxe4X7t374aXBnR5eHiwkMAVMIOD7Cz4VeyjrxC4hdEkXDc3NzcME69fv+7t7T0zM8P8M8QcGhoqXNkBSp04cYLtwwt855132FVATcAM40skCU4hsBcTE0PM2+XWAAAJRklEQVR1ZFz7Ip6RSKazN5IpBQ8pISHBTans7OyhoaHw8HCACv4WnCpPT08QBZBjXxeDI1VdXQ1WgXmFhYV8hgPgyczMhEcFsOHgnTt3gCvsIDBCIn72ZS9cAuc2Njbm5eWlpKSwc0dHR3Gcfay5trbW3d0dF2JfI8vPz2fT+CQj2hfxjEQynb2RSCT57It4RiKZzt5IJJJ89kU8I5FMZ28kEkk++yKekUimszcSiSSffRHPSCTT2RuJRJLPvohnJJLp7I1EIslnX8QzEsl09kYikeSzL+IZiWQ6eyORSPLZF/HMVvX446hvxTPPWHxGPv3pBxkJDLQIeyNRY9t8pac/yIXlt0zimTpt3fpB7X7iEwpn54/9VFmp+NznPvj1q1+1qlw/8shHPDt58oPso6FbYKMmnm2CYA6s5NHFi5oNmhPaEvsVxmVNEjY21m+gf7A4If3EM6sV+nRWu6qtc9u2j34CAEwmmAp6BFllAp6ZIBcK4tkmibUftj355Md+Yq4/2+SbAECNIw0mrnej82xTckE8s2YxnrGZBGzCPp0ZLfvJNDwDQXlKTNAfydTdmCwXCuLZJkloGvjLVVn5gXPGfpKVZ3ygabLaN3pj25RcEM+sWYxnaE9sCoUPNtksM4yTBxCewswVv2I0ChvmDUU4bkWEcH2YWOTOzh+NXoUnKj7OAPzEsYpLYEPMbOaTpQe/sgjxr2h0rClt2BFemsUm9M941cuRC34in6divyLxrPvDcWE8SBif6cUOouVCYljyeNUIuxj8yi+BE0UTyJttb9YjPh5i1cfLmU1poApEAybW/DjqhJyDo8PrWtRoeeMX1riwX+YNFTvCkaheVqMlbVoaG/PPeLdgJrng1ocwQkCigvjgA2eJeIZfhTdWuL0TzyyYZ8wU+WCT1TqaiIhnvDWozlIKMcDvLmj6iUXOwKmWAR/WipqN359gG+/utaSN9/LCjdmVaLwmRy7UnijKBYtHbS74nRgYLb+KcGOmi4uK4hR2tcQzOXjGRja87li3iAYp4hnvLlVnKTW1KE2NXzi4EfFA+4marEZT2rQ3NlG3YIa5wMbIxAesoo3DTPUSlnArnXimlWd8qoT1gGwfTUHYcBFG1IGyFs/aDQ7iXDYu461EaP9stMXpwuLkOFE74cCxhGvxFLJ4uL2xXkNL2viKJg4w4YkinsmRC9GJ3HQZpYTx8KRygLFfGVP5HU0Wj+hfBkLu6rGK27yFPDbBM17vKHN+I1bx8Qlt1or4yhF2Cr+3ikrkbYbVoAgSvPFrmcPkzpO+VqMlbdobm4hnm5sLljZuX9z2GRrZmIPlESeK/DPhVA03N0tYyEM808ozXvH4y1u5KAC3XrVOAJqL0OVXJQFvxEKzkeKfcVMRxSMxbaoz5sJ4RL/KkQstyRYlQDWpwiOqc7/C8lHrBW7eCjSb4Jniw1Xs6FL5lIYogHDJlXBjww7UHfpQodshIgFv/GoHKFo8GylWoyVt2hubahve9FyI7onwI2rNVkRNTd4z8cyCeSa8PcsHKVKYwdqc2tkJLSQQlramO08b5xmO68UzOXKxiTwz5cJU2+QZqxSMG/iUhhSeITCYwd1xtVWmlgTCZiO88yScGNggz1japPPMTHJhRJ5ZwpOpxDNdPBP15sJpK1HD1TI3yOyZz05IJIGIB3w2Rnqb1pI20SQeArCuRy3P5MiFdJ7xuX7RfCNzs3h6WPL4s4Msy8y9Fi0tMSd7s06eCXtz0b1k4WyY6pNqvOrxE6syVoNSSKB9ZaB0q9GSNu2NTTUxm5gLljbV+UbmZvH5RiRPuC5M2ONZ4KsViGfqpGm5B58QEAVQ6wQwqS5G0JcETMInt6S3ae1pE/2khWdy5EI6zzTlgs3o8rsIooyw8lHroW6eodoKzxSCxQj8voswgGqt8dpXu1RBIgm0rHGXbjVa0qa9sQkjMc9c8GUdqnbBAgvjUTvhRDyzPLGhDacXXyPHa1QUgE1ECN043mujWfOVtXxNPBNzMtTeedIuUWJE8Yjm4rWkjTs6whuEatfry5EL0Ymitc6ieES5EK08FiYPwVgJ8ADsNobqwkjimXElWjXAmhObplMbgN2UFfa5vNFyb56tlRc2DFHjl77ARy+r0ZI2LY1N1IbNKhfMcoUepzB5qCyGRuGvouWRlrBkn3hG+kDv5LzjXuI+PDtMRWFKeyORSPLZF/HMFlXcWfwnfn+yJWDLj07/iErDlPZGsg7RcNA87Yt4ZnNaWVv5UcyPtvhu2XJgy4lbJ6hATGlvJCsQDQfN1r6IZzan9HvpW3y2gGePHn90bnmOCsSU9kaydNFw0Jzti3hmc9b4w5gfPrBGry0AGxWIie2NZOmi4aA52xfxzCat8cCWn539GZWG6e2NZNGi4aCZ2xfxzIa0sLLwxKknYI1/5P1HlzsuU4GY3t5IFi0aDpq5fRHPrFMVfRWqkyHB5cEwRbLGTbQ3kuWKhoPmb1/EMytU42jjX4X81VNxT9WP1PODo3Ojf3f47zC6/GOfPyZr3Cx7I1mEaDhoofZFPLNC/TLll1sCHtyy/vOAPw+6HjS/Mo+DgdcDmTW+kPYCFdFm2RvJ/EXDQcu1L+KZFSq/Lf/RY49u8duyxfsBwH546ocXWy9+KeJLINxfBP5F81gzFdFm2RvJ/EXDQcu1L+KZder+wn2HAodP+H3iwVos3y1/5PNHW7weWOOu/F1UOJtobyTzFw0HLde+iGfWrKtdV78T9Z0H40rvByuMYY1tE21ULJtobySLEA0HLdS+iGdWrrnlOa8rXp8K+NSWQLLGzbc3kgWJhoMWZ1/EM5tQ9WD1fyf+973Re1QUm2tvJMsSDQcty77U8OyLMuvLX/7yj+XXc88996r88pBfQUFBMfIrLy+vRGZdu3atU35NTk4Sz0jGFQ0HLZhnJBJJux5++GEpQ7eNDBBp2EfDPhsZ9snLM71iHB0dlbvo5W5AOTk5cpsBjE1ue5a7S3rhhRfk7lsfffRRuecGiMQkkrkN+zZozhp5RiKRNqKFhQW5h3c3b96Ue4Qn9/Du+PHjcg/vtm/fLvcI7+mnn5Z1ePfEE0/IPbz71Kc+ZenIREERz0gkEokku3p7e2Ud3g0ODgovRzwjkUgkkjWIeEYikUgkaxDxjEQikUjWIOIZiUQikaxB/x/lwlPCnRVJiQAAABJ0RVh0RVhJRjpPcmllbnRhdGlvbgAxhFjs7wAAAABJRU5ErkJggg=="}}},{"cell_type":"markdown","source":"In continuous variables , we can use either CDF or PDF to give us a probability for each value. The last time we used CDF , this time we will use PDF (we will use seaborn to display PDF of continuous variables)\n\nThe following graph show the Cdf of Normal distribution :\n![cdfnormal.png](attachment:cdfnormal.png)","metadata":{},"attachments":{"cdfnormal.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"Let's work now , We will work on the data of the Rio de Janeiro Olympics 2016. And we will show the heights of volleyball and basketball players","metadata":{}},{"cell_type":"code","source":"sports_hall = ['Volleyball' , 'Basketball']\nbasket_volley = df_olympic[(df_olympic['Year'] == 2016) & df_olympic['Sport'].isin(sports_hall)]","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sns.set_style(\"darkgrid\")\nfig, ax = plt.subplots(figsize=(15,8))\nsns.distplot(basket_volley['Height'] , kde = True , hist = False)\n\n# label the axis\nlabel_graph(15 , 'Players Heights' , 'Probability density (PDF)' ,'Normal Distribution' ,  20 )","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"np.std(basket_volley['Height'])","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"As you can see, these data are distributed in a normal distribution, and the y-axis represents the probability. \n\nFor example, the probability of finding a player with a height of 190 meters (the average height of the players) is around 0.035 and its on.\n\nAlso we can use Cdf to represent this data ","metadata":{}},{"cell_type":"code","source":"#fig, ax = plt.subplots(figsize=(12,8))\n\n#players_heights = Cdf.from_seq(basket_volley['Height'])\n#players_heights.plot()\n\n# label the axis\n#label_graph(18 , 'Players Heights' , 'CDF' ,'Cdf for Normal Distribution' ,  20 )","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Normality test\nWe just talked about the normal distribution, but what if we want to know whether our data follows the normal distribution or not?\n\nWe can test the Normality in many ways, but we will focus on visualization only this visualize called quantile-quantile or Q - Q plot ","metadata":{}},{"cell_type":"code","source":"stats.probplot(basket_volley['Height'], dist = 'norm' , plot=plt) \nplt.show()","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"The blue dots represent our data and the diagonal line represents the normal distribution. If the data points follow the diagonal line, the data will be normally distributed. The further away the data points are from the diagonal line, the farther our data is from the normal distribution. In the graph above, our data follows the diagonal line, so it is Normally distributed, but in the following graph.\n\nlet's see another example.","metadata":{}},{"cell_type":"code","source":"sns.set_style(\"darkgrid\")\nsns.distplot(df_house['SalePrice'], fit=stats.norm)\nfig = plt.figure()\nstats.probplot(df_house['SalePrice'], plot=plt)","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"the data points do not follow the diagonal line, so they do not follow the normal distribution. the distribution of this data is lognormal distribution","metadata":{}},{"cell_type":"markdown","source":"## Normal Versus Lognormal distribution \nBoth normal and lognormal distributions are used in statistical mathematics to describe the probability of an event occurring.\nBut there are many difference between them \n\n1- The shape of normal distribution is symmetric distribution whereas the lognormal distribution shape is positive distribution, they create a right-skewed curve. \n\n2 - In the normal distribution The mean , the median and the mode are all the same whareas in lognormal  mean > median > mode \n![lognormal-distribution.png](attachment:lognormal-distribution.png)\n\nLet's see the lognormal distribution from our data\n","metadata":{},"attachments":{"lognormal-distribution.png":{"image/png":"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Why we need to transform lognormal distribution to normal distribution ?\nNow you know that the natural logarithm is skewed to the right, and this is not good for us, because we will enter this data later into a model for machine learning, and the skewed data has some negative effects on our data and on the model,\n\nfor example:\n\n1- When your data is skewed, the average of the data is different from the median, and this can make the mean misleading because the values are not close to the mean\n\n2- The skewed data causes outliers values, which lead to spoil and mislead the training process resulting in longer training times, less accurate models and ultimately poorer results. for example , in linear regression model it can change the model equation completely i.e. bad prediction or estimation \n\nIn order to transform lognormal distribution to a normal distribution We take the log of each point in our data ","metadata":{}},{"cell_type":"code","source":"df_house['SalePrice'] = np.log(df_house['SalePrice'])\nsns.distplot(df_house['SalePrice'], fit= stats.norm)\nfig = plt.figure()\nstats.probplot(df_house['SalePrice'], plot=plt)","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Another code to perform Q-Q plot :","metadata":{}},{"cell_type":"code","source":"import statsmodels.api as sm\nfig = sm.qqplot(df_house['SalePrice'], line='s')\nplt.show()","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 9-Student's t (T-Distribution) :\nStudent's T or T-distribution is a continuous probability distribution and is a way of describing data that follow normal distribution \n\nthe t-distribution is used to:\n\nFind the critical values for a confidence interval when the data is approximately normally distributed.\nused in t-tests and regression analysis.\n\nThere are several conditions for using T-Distribution:\n\n1-Data follows a normal distribution.\n\n2-The sample size should be less than 30.\n\n3-The population variance or standard deviation is unknown (The variance in a t-distribution is estimated based on the degrees of freedom of the data set (total number of observations minus 1).\n\nIf we know the population standard deviation , we can use a z-distribution (we will apply a z-distribution)","metadata":{}},{"cell_type":"markdown","source":"## 11- Standard normal distribution (Z-Distribution) :\nStandard normal distribution also called Z-distribution is a continuous probability distribution and is a special normal distribution where the mean of the Z-distribution is always 0 and the standard deviation = 1.\n\n![standard-normal-distribution-1024x633.png](attachment:standard-normal-distribution-1024x633.png)\nAny normal distribution can be converted to a Z-distribution by converting its values into a z-score . A z-score gives you an idea of how far from the mean a data point is.\n\nif value above the mean the z-score is positive and negative if it lies below the mean \n\nZ-score equation : 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"}}},{"cell_type":"markdown","source":"![Z-score-formula.jpg](attachment:Z-score-formula.jpg)\nLet's take an example of the Z-distribution (we will work on the heights of the players)\nIf we draw a player at randomlly. What is the probability that the height of the player will be above than 195 centimeters ?\n\nFirst , Determine two parameters:\n\n1-Mean of data (here , the average height of the players)\n\n2-the standard deviation\n","metadata":{},"attachments":{"Z-score-formula.jpg":{"image/jpeg":"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= np.mean(basket_volley['Height'])\nstd = np.std(basket_volley['Height'])\n\ncdf_195 = stats.norm(loc = mu , scale = std).cdf(195)\nprobability = 1- cdf_195\nprint('The probability is {} or {}%'.format(round(probability , 2) , round(probability*100 , 2)))","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"stats.norm(loc = 80 , scale = 10).cdf(105)","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Another example:\n\nWhat is the probability that the height of the player will be smaller than 170 centimeter ?","metadata":{}},{"cell_type":"code","source":"prob = stats.norm(loc = mu , scale = std).cdf(170)\nprint('The probability is {} or {}%'.format(round(prob , 2) , round(prob*100 , 2)))","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"last example:\n\nwhat is the probability that the height of the player will be between 170 and 185 centimeter ?","metadata":{}},{"cell_type":"code","source":"cdf_upper = stats.norm(loc = mu , scale = std).cdf(185)\ncdf_lower = stats.norm(loc = mu , scale = std).cdf(170)\n \nprob = cdf_upper - cdf_lower\nprint('The probability is {} or {}%'.format(round(prob , 2) , round(prob*100 , 2)))","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 12- Pareto distribution :\n\nThe Pareto Distribution was named after Italian economist and sociologist Vilfredo Pareto. It is sometimes referred to as the Pareto Principle or the 80-20 Rule.\n\nIn Pareto distribution, we pay attention to the most common problems and solve them.For example, in one of the agricultural countries, the farmers complain about some agricultural problems to the government to solve these problems. The government collected the various complaints of the farmers and we found that 97 of the farmers complain about the quality of the fertilizers, 140 about the irrigation systems, 58 about the agricultural seeds, 6 about the scarcity of water and 17 about the salinity of the soil. \n\n##### step 1 :\nfirst create the data using dataframe","metadata":{}},{"cell_type":"code","source":"data = pd.DataFrame({'Count' : [97 , 140 ,58 , 6 , 17]})\ndata.index = ['compost quality' , 'irrigation network' , 'agricultural seeds' , 'Water scarcity' , ' soil salinization']","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"##### step 2 :\narrange the problems in descending order and then calculate the cumulative percentage","metadata":{}},{"cell_type":"code","source":"#sort DataFrame by count descending\ndata = data.sort_values(by='Count', ascending=False)\n\n#add column to display cumulative percentage\ndata['cumulative'] = data['Count'].cumsum()/data['Count'].sum()*100","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"##### Step 3 :\nplot a Pareto graph","metadata":{}},{"cell_type":"code","source":"sns.set_style('white')\nfig, ax = plt.subplots(figsize = (15 , 8))\nax.bar(data.index, data['Count'], color='b')\n\n#add cumulative percentage line to plot\nax2 = ax.twinx()\nax2.plot(data.index, data['cumulative'], color='r', marker=\"D\", ms=4)\nax2.yaxis.set_major_formatter(PercentFormatter())\n\n#specify axis colors\nax.tick_params(axis='y', colors='b')\nax2.tick_params(axis='y', colors='r')\n\n#display Pareto chart\nplt.show()","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"As you can see in the graph above, we will give our full attention at the beginning to solve the problem of irrigation networks and compost quality\n\nYou can also implement a Pareto chart directly through this package :\nhttps://pypi.org/project/paretochart/?fbclid=IwAR3lovL5j4qyirC3vCBbd1pRXDX7qdyy6RehhGHREGAFq8J8nzCOXq0VOaw","metadata":{}},{"cell_type":"markdown","source":"We did a great job together on probability distributions and now you have learned some concepts that can help you in your own business and projects. I hope you enjoyed this notebook and remember that there is more to learn in statistics and probability to be a unique data scientist.","metadata":{}}]}