Table of Contents
Chapter 1 - Histograms & Charting…………………………......………..………….....
• Creating a Chart………………………………………………....…………………………......
• Creating Descriptive Statistics………………………………........………….....….....….......…
• Creating a Histogram………………………………………………………......……………….
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Chapter 2 - Combinations & Permutations…………………….....……………..........
• Basic Explanation of Combinations and Permutations………………….............…...……………
• Difference Between Combinations and Permutations…………………................………………
• Combination Formulas……………………………………………………........…....…………
• Excel Functions Used When Calculating Combinations……………………................…………
• COMBIN (n,x)………………………………………………………….......…....…...………
• FACT (n)……………………………………………………………........……...........………
• Permutation Formulas…………………………………………………….................…....……
• Excel Functions Used When Calculating Permutations………………………….................….…
• PERMUT (n, x)………………………………………………………………...…........…...…
• FACT (n)…………………………………………………………………….......................…
• Combination Problems…………………………………………………………............……...
• Problem 1: Combinations of Investment Proposals……………………....………..............……
• Problem 2: Combination of Newly Opened Offices…………………………..........…...........…
• Problem 3: Combinations of Multiple Newly Opened Offices……………….….................……
• Problem 4: Combinations of Committees…………………………….......…………......………
• Problem 5: Combinations of Sub-Groups……………………………......………………..……
• Permutation Problems……………………………………………….....……………....………
• Problem 6: Permutations of Delivery Routes………………………........………………....……
• Problem 7: Permutations of Seating Arrangements………………….........………………..……
• Problem 8: Permutations of Executive Groups……………………….......………………..……
• Problem 9: Permutations of Book Arrangements…………………….......………………...……
• Problem 10: Permutations of Letter Groups………………………….………………............…
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Chapter 3 - Correlation & Covariance………….………...………………....…….…..
• Basic Explanation of Correlation and Covariance……………….…..…………………..........…
• Correlation Analysis…………………………………………....………………………....……
• Positive Correlation vs. Negative Correlation…………………………..……………….........…
• Calculation of Correlation Coefficient…………………………...…………………….......……
• Excel Functions Used When Calculating Correlation Coefficient………..…………….............…
• CORREL (Highlighted Blocks of Cells of 2 Variables)……………….…...…………….........…
• Problem 1: Calculating Correlation Between 2 Variables …………….……….……...............…
• Tools / Data Analysis / Correlation……………………………………...….…………......……
• Problem 2: Calculating Correlation Between Multiple Variables………...…………................…
• Covariance Analysis…………………………………………………………………........……
• Calculation of Covariance Page…………………………….………...………........…..….....…
• Excel Functions Used When Calculating Covariance………….……………...…...........….....…
• COVAR (Highlighted Blocks of Cells of 2 Variables).…………...………..….................….......
• Problem 3: Calculating Covariance Between 2 Variables……………......…..………...........…..
• Tools / Data Analysis /
Covariance…………………………………..........................................
• Problem 4: Calculating Covariance Between Multiple Variables…...………………….............…
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Chapter 4 - Normal Distribution………….…………………….……....................……
• Basic Description of Normal Distribution……………………………..………………...........…
• Mapping the Normal Curve…………………………………………….………………….......
• The Standardized Normal Curve………………………………………...………………..........
• The "68 - 95 - 99.7%" Rule……………………………………………….....…………….......
• "Six Sigma Quality" in the Corporate World……………………………….……………...........
• The 4 Most Important Excel Normal Curve
Functions…………………………..………...........
• NORMDIST (x, Mean, Standard Dev, TRUE)……………………………...……………........
• NORMSDIST (x)………………………………………………………...……………………
• NORMINV (% of area to left of x, Mean, Standard
Deviation)……………...........……………
• NORMSINV (% of area to the left of x)…………………………………..……….......………
• Problem 1: Using the Normal Distribution to Determine Probability of Daily
Sales
Below a Certain Point…………………………………………………….……...……........…
• Problem 2 : Using the Normal Distribution to Determine Probability that
Fuel
Consumption is in a Certain Range…..………………………………...……………............…
• Problem 3: Using the Normal Distribution to Determine Upper Limit of
Delivery Time………….....……………………………………………….…………......……
• Problem 4: Using Normal Distribution to Determine Lower Limit of Tire
Life……...….................
• Problem 5: Using Normal Distribution to Determine Boundaries of a Range
of Tire Life…….…………………………………………………………………….....…..…
• Problem 6: Using Normal Distribution to Determine Probability of a
Pumpkin's
Weight Being in 1 of 2 Ranges……....……………………………………………...........……
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Chapter 5 - Normal Distribution….....................…………...……........………………..
• Basic Description of t Distribution…………………………………….………...........…………
• Degrees of Freedom………………………………………………………...……........………
• One Very Important Caution About Using the t Distribution…………..……….............……..…
• The Normal Distribution and Large Samples………………………….........….….............…….
• Estimating Confidence Intervals with the t Distribution……………….……….............…………
• Levels of Confidence and Significance…………………………………….................…………
• Population Mean vs. Sample Mean…………………………………….………..……..........…
• Standard Deviation and Standard Error…………………………………...………............……
• Region of Certainty vs. Region of Uncertainty……………………………......…............………
• t Value…………………………………………………………………………...……………
• Excel Functions Used When Calculating Confidence Interval…………………........…….......…
• COUNT (Highlighted Block of Cells)…………………………………..…………........………
• STDEV (Highlighted Block of Cells)………………………………....…………...........………
• AVERAGE (Highlighted Block of Cells)…………………………..……………….......………
• TINV (a)…………………………………………………….…………....………..…………
• Formula for Calculating Confidence Interval Boundaries………...….……………..............……
• Problem: Calculate a Confidence Interval Based on Small Sample
Data Using the t Distribution………………………...…………………..…….........…………
• t Test and Hypothesis Testing……………………...…………………….…………..........……
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Chapter 6 - Binomial Distribution...................................................................................
• Basic Explanation of Binomial Distribution…………………………..………….............………
• Bernoulli Trial…………………………………………………………...………......…………
• Bernoulli Process…………………………………………………………………........………
• Bernoulli Distribution…………………………………………………...........…………………
• Binomial Distribution Parameters……………………………………….…............……………
• Random Variable……………………………………………………………...………………
• Count of Successes per Trial……………………………………………….…..........…………
• Population Proportion……………………………………………………...…......……………
• Sample Proportion……………………………………………………………..............………
• Sample Size…………………………………………………………………….......….………
• Expected Sample Occurrence Parameters…………………………………...............…………
• Expected Sample Occurrence Mean………………………………………....……...........……
• Expected Sample Occurrence Variance…………...……………...…………............…………
• Expected Sample Occurrence Standard Deviation………………………...............……………
• Expected Sample Proportion Parameters…………………………...............…..............………
• Expected Sample Proportion………...…………………………………………...............……
• Expected Sample Proportion Variance……………………………………………........………
• Expected Sample Proportion Standard Deviation………………………………................……
• Probability Density Function vs. Cumulative Distribution Function………...….................………
• Binomial Probability Density Function…………………………………………….........………
• BINOMDIST (k, n, p, FALSE)…………………………………………………..….......……
• Binomial Cumulative Distribution Function……………………...……………...............………
• BINOMDIST (k, n, p, TRUE)………………………………………………………….......…
• Problem 1: Probability of Getting a Certain Number of
Successes for Binomial
Variable Trials…...……………………………………................……
• Problem 2: Probability of Getting a Certain Range of
Successes for Binomial
Variable Trials……..……………………………….............…………
• Problem 3: Probability of Getting a Certain Range of
Successes for Binomial
Variable Trials……..…………………………….............……………
• Estimating the Binomial Distribution with the Normal and Poisson
Distributions.......................…..
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Chapter 7 - Confidence Intervals.....................................................................................
• Basic Explanation of Confidence Intervals……………………………...........…………………
• Mean Sampling vs. Proportion Sampling………………………….....……............……………
• Confidence Intervals of a Population Mean…………………………..................………………
• Calculate Confidence Intervals Using Large Samples……………………...............……………
• The Central Limit Theorem……………………………………………..……….......…………
• Levels of Confidence and Significance…………………………………..…...............…………
• Population Mean vs. Sample Mean…………………………………….............………………
• Standard Deviation and Standard Error…………………………………...............……………
• Region of Certainty vs. Region of Uncertainty……………………………..............……………
• Z Score………………………………………...……………………………...…........………
• Excel Functions Used When Calculating Confidence Interval of
Mean….....……................……
• COUNT (Highlighted Block of Cells)………………………………………….........…………
• STDEV (Highlighted Block of Cells)……………………………………………...........………
• AVERAGE (Highlighted Block of Cells)………………………………………….........………
• NORMSINV (1 - a/2)…………………………………………………………………...……
• CONFIDENCE (a, s, n)………………………………………………………………....……
• Formulas for Calculating Confidence Interval Boundaries from Sample
Data……................……
• Problem 1: Calculate a Confidence Interval from a
Random Sample of Test
Scores………..…………………....……………..........……………
• Problem 2: Calculate a Confidence Interval of
Daily Sales Based Upon
Sample Mean and Standard Deviation……….....................…………
• Problem 3: Calculate an Exact Range of 95% of Sales Based Upon the
Population Mean and Standard Deviation……………………………………..…............……
• Determine Minimum Sample Size to Limit Confidence Interval of Mean to a
Certain Width……………………………………………..……………………….....………
• Problem 4: Determine the Minimum Number of Sales Territories to Sample
In Order To Limit the 95% Confidence Interval to a Certain
Width….………...................……
• Confidence Interval of a Population Proportion…………………………………...........………
• Mean Sampling vs. Proportion Sampling……………………………….................……………
• Levels of Confidence and Significance…………………………………....…............…….……
• Standard Deviation and Standard Error…………………………………...…...........…….……
• Region of Certainty vs. Region of Uncertainty…………………………...…..............…….……
• Z Score……………………………………………………………………..…...…....….……
• Excel Functions Used When Calculating Confidence Interval of
Proportion…......................……
• COUNT (Highlighted Block of Cells)………………………………………...……..........……
• NORMSINV (1 - a)……………………………………………………………………..……
• Formula for Calculating Confidence Interval Boundaries from Sample
Data………..................…
• Problem 5: Determine Confidence Interval of Shoppers Who
Prefer to Pay By Credit Card Based Upon Sample Data…………………………................…
• Determine Minimum Sample Size to Limit Confidence Interval
of Proportion
to a Certain Width……………………………………..………..............………
• Problem 6: Determine the Minimum Sample Size of Voters to be 95% Certain
that the Population Proportion is only 1% Different than
Sample Proportion…....................……
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Chapter 8 - Hypothesis Tests - Means............................................................................
• Basic Explanation of Hypothesis Testing of Means……………………………..................……
• The Four-Step Method for Solving All Hypothesis Testing
Problems…………...............………
• The Four Ways of Classifying All Hypothesis Test Problems………………….…..............……
• Mean Testing vs. Proportion Testing…………………………………………….......…………
• One-Tailed vs. Two-Tailed Testing…………………………………………….............………
• One Sample vs. Two Samples………………………………………………….….......………
• Unpaired Data Testing vs. Paired Data Testing……………………………….…...........………
• Detailed Description of the Four-Step Method for
Solving Mean Testing
Problems…...…………………………………………..............………
• Initial Steps…………………………………………….…………………………...........……
• Problem Classification………………………………..……………………………......………
• Mean Testing vs. Proportion Testing……………….........…………………………..............…
• One-Tailed vs. Two-Tailed Testing…………………………..…………..…….........…………
• One Sample vs. Two Sample Testing……………………………………...…...........…………
• Unpaired Data Testing vs. Paired Data Testing…………………….……….…..............………
• Information Layout……………………………………………..……….………......…………
• Level of Significance…………………………………………………...…….......……………
• Comparison Sample Data………………………………………….………….........…………
• The Four Steps to Solving All Hypothesis Testing Problems……………….…...............………
• Step 1 - Create Null and Alternate Hypotheses……………………………...........……………
• Step 2 - Map the Normal Curve…………………………………..………….......……………
• Step 3 - Map the Region of Certainty……………………………………..…........……………
• Mapping the Region of Certainty for a Two-Tailed Test……………………..…............…....…
• Mapping the Region of Certainty for a One-Tailed Test……………………..….............………
• Step 4 Perform Critical Value and p-Value Tests……………….…………..….............………
• Critical Value Test………………………………………………………...…..........…………
• p Value Test…………………………………………………………....………......…....……
• Type 1 and Type 2 Errors…………………………………………………………......………
• Problem 1: Two-Tailed, One Sample, Unpaired Hypothesis Test of Mean
Testing a Manufacturer's Claim of Average Product
Thickness……………...................………
• Problem 2: One-Tailed, One Sample, Unpaired Hypothesis Test of Mean
Testing Whether a Delivery Time Has Gotten
Worse………..………………...............………
• Problem 3: Two-Tailed, Two Sample, Unpaired Hypothesis Test of Mean
Testing Whether Wages Are the Same in Two
Areas……..…………….…..............…………
• Paired Data………………………………………………………………………....…………
• Problem 4: One-Tailed, One Sample, Paired Hypothesis Test of Mean
Testing Whether an Advertising Campaign Improved
Sales………………....................………
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Chapter 9 - Hypothesis Tests – Proportions……………….............……..…………..
• Basic Explanation of Hypothesis Testing of Proportions……………………...............…………
• The Four-Step Method for Solving All Hypothesis Testing
Problems……………...............……
• The Four Ways of Classifying All Hypothesis Test Problems…………………...............………
• Mean Testing vs. Proportion Testing……………………………………………...........………
• One-Tailed vs. Two-Tailed Testing…………………………………..……...........……………
• One Sample vs. Two Samples……………………………………….……...........……………
• Unpaired Data Testing vs. Paired Data Testing………………………….…..............…….……
• Detailed Description of the Four-Step Method for Solving
Proportion
Testing Problems……………………........…………………….........……………
• Initial Steps…………………………………………...……………………….....……………
• Problem Classification………………………………...………….………........………………
• Mean Testing vs. Proportion Testing………………….……………………..........……………
• One-Tailed vs. Two-Tailed Testing…………………..………….……….…….........…………
• One Sample vs. Two Sample Testing………………………………………….........…………
• Unpaired Data Testing vs. Paired Data Testing…………………......……….............…………
• Information Layout…………………………………………..…………..…………....………
• Level of Significance……………………………....………………...…………….......………
• Comparison Sample Data……………………………………......…………………........……
• The Four Steps to Solving All Hypothesis Testing Problems……..…...…………...............……
• Step 1 - Create Null and Alternate Hypotheses……………………………………..........……
• Step 2 - Map the Normal Curve……………………………………..……………......………
• Step 3 - Map the Region of Certainty………………….….…………..……..…….......………
• Mapping the Region of Certainty for a Two-Tailed Test……..………....……............…………
• Mapping the Region of Certainty for a One-Tailed Test……..……………............……………
• Step 4 Perform Critical Value and p-Value Tests……………..…..…………............…………
• Critical Value Test……………………………………….……..…………………….......……
• p Value Test…………………………………………………….…………….........…………
• Type 1 and Type 2 Errors……………………………………...……………….......…………
• Problem 1: Two-Tailed, One Sample, Unpaired Hypothesis Test of Proportion
Testing Employee Preferences in Two
Companies………………….…..…...............…………
• Problem 2: One-Tailed, Two Sample, Unpaired Hypothesis Test of Proportion
Testing Effectiveness of Two Drugs………………………………….………..............………
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Chapter 10 - Excel Hypothesis Tools………………………………..........……………
• t-Test: Paired Two Sample for Means…………………………………...…..........……………
• t-Test:Two-Sample Assuming Unequal Variances……………………..….............……………
• t-Test: Two-Sample Assuming Equal Variances……………….....………..............……………
• z-Test: Two Sample for Means……………………………………..…………….........………
• ZTEST…………………………………………………………………...……………....……
• TTEST…………………………………………………………………...…....………………
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Chapter 11 - Prediction Using Regression………….....………............…..………….
• Basic Explanation of Regression……………..…………….……………...........………………
• The Regression Equation………………………………….…………..…..........………………
• Regression is for Predicting, Not Forecasting……………………….………..............…………
• Performing Multiple Regression in Excel…………………...…………...……............…………
• 1st Regression Step - Graph the Data……………………………..…………...........…………
• 2nd Regression Step - Run Correlation Analysis…………………...….……..............…………
• 3rd Regression Step - Run Regression Analysis………………………………...............………
• 4th Regression Step - Analyze the Output……………………………………............…………
• The Regression Equation………………………………..……………….…………..........……
• Using the Regression Equation to Predict an
Output…….....………….......……….............……
• The Confidence Interval of the Output Variable………………...........…………………………
• R Square…………………………………………………………….......…….………………
• Adjusted R Square…………………………………………………….…....…………………
• F Statistic……………………………………………………………..…….....………………
• ANOVA Calculation of the Regression Output………………………….………..................…
• P Values of the Regression Coefficients and Intercept…..………………………................……
• Regression Using Dummy Variables………………………………………………............……
• Creating Dummy Variables for Attributes of Multiple
Choices….…..………...............…………
• Removing a Dummy Variable to Prevent Co-Linearity……………..…...……................………
• Conjoint Analysis Done With Regression Using Dummy Variables….….….................…………
• 1st Conjoint Step - List Product Attributes………………….……………...…..........…………
• 2nd Conjoint Step - List All Attribute Combinations……………………….…...........…………
• 3rd Conjoint Step - Conduct Consumer Survey…………………………...………...............…
• 4th Conjoint Step - Create Dummy Variables for Attributes…………...……….............………
• 5th Conjoint Step - Remove 1 Dummy Variable from Each Set of
Attributes……...............……
• 6th Conjoint Step - Run Regression Analysis…………………………………..........……….…
• 7th Conjoint Step - Analyze the Output………………………………………..…….........……
• Showing the Removing Dummy Variables Did Not Affect
Output…....……….……..............….
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Chapter 12 - Independence Tests & ANOVA……………………...…...........………
• Basic Explanation of ANOVA……………………………………………........………………
• ANOVA Tests the Null Hypothesis - That Nothing Is Different Between
Groups….............……
• Overview of ANOVA in Excel…………………………………………………….......………
• Single Factor ANOVA……………………………………………………….......……………
• Two-Factor ANOVA Without Replication………………………………………..........………
• Two-Factor ANOVA With Replication………………………….……………….........………
• ANOVA:Single Factor Analysis……………………………………..…..….….........…………
• Problem: 3 Sales Closing Methods and Single Factor ANOVA……………...............…………
• Problem Solving Steps…………………………………………………..…..........……………
• Analyze the Output………………………………………………………….............…………
• ANOVA: Two-Factor Without Replication……………………………………....……………
• Problem: 3 Sales Closing Methods, 5 Salespeople, and Two-Factor ANOVA
Without Replication…………..……………………………………….....……………………
• Problem Solving Steps………………………………………………..….........….……………
• Analyze the Output………………………………………………………….......…..…………
• ANOVA:Two Factor With Replication…………………………………...………........………
• Problem: 3 Ad Headlines, 3 Ad Texts, their Interaction, and Two-Factor
ANOVA
With Replication…………………………………………………….……….......……………
• Problem Solving Steps………………………………………………...…..................….......…
• Analyze the Output…………………………………………………..….…………..............…
• ANOVA: Single Factor Analysis Calculated by Hand……………….……….........................…
• Problem: 3 Closing Methods and Single Factor ANOVA Calculated By
Hand….................……
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Chapter 13 - Chi-Square Independence Test…………................……………………
• Basic Explanation of the Chi-Square Independence Test………………..…...............…………
• Level of Certainty………………………………………………………….......………………
• Level of Significance……………………………………………………….......………………
• Contingency Table………………………………………………….......……………...………
• Degrees of Freedom……………………………………………….........………..……………
• Chi-Square Distribution………………………………………………….......…...……………
• Critical Chi-Square Statistic……………………………………………...........….……………
• Independence Test Rule…………………………………………………….........……………
• Excel Functions Used When Performing the Chi-Square Independence
Test…....................……
• CHIINC (Level of Significance, Degrees of Freedom)………………………….............………
• CHIDIST (Critical Chi-Square Statistic, Degrees of Freedom)……………............……………
• Problem: Determine if There is a Relationship Between the Time Spent in a
Store and the Amount of Items Purchased….…………………………………...............……..…
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Chapter 14 - Variance of Population Test……………………...........……..…………
• Basic Explanation of the Chi-Square Variance Change Test……………….................…………
• The 5-Step Chi-Square Variance Change Test……………………………..…..........…………
• 1st Variance Test Step - Determine the Level of Certainty and
a…………......................………
• 2nd Variance Test Step - Measure Sample Standard Deviation………….…..................………
• 3rd Variance Test Step - Calculate the Chi-Square
Statistic………………....…................….…
• 4th Variance Test Step - Calculate the Curve Area to the
Outside of the
Chi-Square Statistic....……………………………..….…….........…….………
• 5th Variance Test Step - Analyze Results Using the
Chi-Square Statistic
Rule…………...…………………………………..….…….........………
• Problem: Using Chi-Square Test to Determine Whether
Population Variance
has Increased…..………………………………..….…...........…………
• Apply the 5-Step Chi-Square Variance Change Test…….………………..............……………
• Problem: Using Chi-Square Test to Determine Whether
Population Variance
has Decreased….………...……………………..….....................………
• Apply the 5-Step Chi-Square Variance Change Test…………………………...............………
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Chapter 15 - Other Useful Distributions……………………...........…….....…………
• Multinomial Distribution…………………………………...………….......……………………
• Hypergeometric Distribution……………………………………………….........……...………
• Poisson Distribution……………………………………….…………………….......…………
• Uniform Distribution……………………………………….……………………….......………
• Exponential Distribution……………………………………...…….…………….……........…..
• Gamma Distribution………………………………………….…………...………........………
• Beta Distribution……………………………………………..…………………......…………
• Weibull Distribution………………………………………….………………….......…………
• F Distribution…………………………………………………...…………….......……………
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Chapter 16 - How To Graph Distributions…………………………...........…………
1) Learning how to graph a generic set of x-y coordinates……………..…............……....………
.
2) Learning how to create the x coordinates and the y coordinates
specific to the type of distribution being graphed……………....................….……………………
• Normal Distribution……………………………………………………........…………………
• Probability Density Function………………………………………………........………………
• Cumulative Distribution Function……………………………………….............………………
• Normal Distribution - Graphing Outer 2% Tails…………………………...........………………
• Probability Density Function…………………………………………………........……………
• t Distribution…………………………………………………….……..........…………………
• Probability Density Function…………………………………...……………........……………
• Binomial Distribution……………………………...……………………….……….......………
• Probability Density Function……………………..……………………………….........………
• Cumulative Distribution Function………………….…………………..........……………..……
• Chi-Square Distribution……………………………...……………………........…………...…
• Probability Density Function…………………………...………………........…………………
• Poisson Distribution………………………………...………………………........…….………
• Probability Density Function………………………..…………………………….........………
• Cumulative Distribution Function………………….……………………………….......………
• Weibull Distribution…………………………………………………….…......………….……
• Probability Density Function…………………………………………..........………….………
• Cumulative Distribution Function…………………………………….………..........……..……
• Exponential Distribution……………………………………………...………...........…………
• Probability Density Function…………………………………………...……........……………
• Cumulative Distribution Function……………………………………………........….…………
• Hypergeometric Distribution…………………………………………............…………………
• Probability Density Function………………………………………...…….........………………
• Beta Distribution…………………………………………………………….......……..………
• Cumulative Distribution Function……………………………………………..........….…..……
• Gamma Distribution…………………………………………………...…........………….……
• Probability Density Function……………………..………………………….........……….……
• Cumulative Distribution Function……………….………………………..............…………..…
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