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Exercises
FINISHED
Reading Stem and Leaf Plots*
Creating Bar Graphs 2*
Read Bar Graphs 1
Read Bar Graphs 2*
Creating Histograms
Reading Histograms
Calculating the Mean
Calculating the Median
Mean, Median and Mode*
Calculating the Mean: Data Displays
Calculating the Median: Data Displays
Effects of Shifting, Adding and Removing a Data Point
Missing Value Given the Mean
Median and Range Puzzlers
Shape of Distributions
Interpreting and Comparing Data Distributions*
Reading Box Plots*
Interpreting Quartiles
Sample and Population Variance*
Standard Deviation of a Population*
Sample and Population Standard Deviation*
Basic Set Notation*
Simple Probability*
Adding Probabilities*
Independent Probability*
Probabilities of Compound Events*
Dependent Probability*
Identifying Dependent and Independent Events*
Multiplying Dependent Probabilities*
Describing Subsets of Sample Spaces*
Constructing Probability Distributions*
Expected Value*
Expected Value with Empirical Probabilities
Expected Value with Calculated Probabilities
Making Decisions with Expected Values
DUE MONDAY, NOVEMBER 7 AT 4:30 PM
Videos
Statistics Intro: Mean, Median and Mode (8:53)*
Finding Mean, Median and Mode (3:55)*
Exploring the Mean and Median (5:25)*
Comparing Means of Distributions (7:49)*
Means and Medians of Different Distributions (6:29)*
Inferring Population Mean from Sample Mean (10:02)*
Box and Whisker Plot (3:18)*
Constructing a Box and Whisker Plot (8:18)*
Finding the Range and Mid-range (2:03)*
Range, Variance and Standard Deviation as a Measures of Dispersion (12:34)*
Variance of a Population (8:05)*
Sample Variance (10:38)*
Review and Intuition Why We Divide by n-1 for the Unbiased Sample Variance (9:44)*
Simulation Showing Bias in Sample Variance (6:24)*
PROGRAM - Unbiased Estimation of Population Variance*
Another Simulation Giving Evidence that n-1 Gives Us an Unbiased Estimate of Variance (4:46)*
Simulation Providing Evidence that (n-1) Gives Us Unbiased Estimate (4:30)*
PROGRAM - Will It Converge Towards -1?*
Population Standard Deviation (8:05)*
Sample Standard Deviation and Bias (9:33)*
Statistics: Standard Deviation (13:07)*
Exploring Standard Deviation 1 Module (3:58)*
Statistics: Alternate Variance Formulas (12:17)*
Probability Explained (8:18)*
READING - Probability - The Basics*
Determining Probability (4:19)*
Describing Subsets of Sample Spaces Exercise (5:44)*
Finding Probability Example (2:56)*
Finding Probability Example 2 (9:56)*
Finding Probability Example 3 (2:11)*
Probability with Playing Cards and Venn Diagrams (10:02)*
Addition Rule for Probability (10:43)*
Compound Probability of Independent Events (6:00)*
Coin Flipping Probability (9:20)*
Die Rolling Probability (5:15)*
Free Throwing Probability (7:05)*
Three Pointer Vs. Free Throwing Probability (5:47)*
Probability without Equally Likely Events (8:58)*
Test Taking Probability and Independent Events (4:44)*
Die Rolling Probability with Independent Events (2:28)*
Dependent Probability Introduction (6:38)
Dependent Probability Example (9:01)
Dependent Probability Example 2 (6:34)
Independent or Dependent Probability Event? (2:39)
Analyzing Event Probability for Independence (6:48)
Analyzing Dependent Probability (9:30)
Calculating Conditional Probability (6:43)
Probability and the Monty Hall Problem (7:23)
Intersection and Union of Sets (7:44)
Relative Complement or Difference Between Sets (6:15)
Universal Set and Absolute Complement (6:26)
Subset, Strict Subset and Superset (4:32)
Bringing the Set Operations Together (6:28)
Random Variables (5:32)
Discrete and Continuous Random Variables (11:57)
Constructing a Probability Distribution for a Random Variable (6:48)
Probability Density Functions (10:02)
Term Life Insurance and Death Probability (4:22)
Getting Data from Expected Value (9:52)
Expected Profit from Lottery Ticket (9:18)
Expected Value While Fishing (8:24)
Comparing Insurance with Expected Value (9:16)
Law of Large Numbers (9:00)
Binomial Distribution (11:52)
Visualizing a Binomial Distribution (9:27)
Probability of Making 2 Shots in 6 Attempts (10:24)
Generalizing k Scores in n Events (4:13)
Free Throw Binomial Probability Distribution (8:39)
Graphing Basketball Binomial Distribution (4:23)
Expected Value of Binomial Distribution (16:56)
Poisson Process 1 (11:01)
Poisson Process 2 (12:42)
Studying, Shoe Size and Test Scores Scatter Plots (2:26)
People Smoking Less Over Time Scatter Plot (2:35)
Constructing a Scatter Plot (2:32)
Constructing Scatter Plot Exercise Example (1:58)
Comparing Models to Fit Data (4:05)
Correlation and Causality (10:45)
Fitting a Line to Data (7:48)
Estimating the Line of Best Fit Exercise (1:17)
Squared Error of Regression Line (6:47)
Proof (Part 1) Minimizing Squared Error to Regression Line (10:35)
Proof (Part 2) Minimizing Squared Error to Regression Line (9:54)
Proof (Part 3) Minimizing Squared Error to Regression Line (10:54)
Proof (Part 4) Minimizing Squared Error to Regression Line (4:18)
Regression Line Example (9:27)
Second Regression Example (9:15)
R-Squared or Coefficient of Determination (12:41)
Calculating R-Squared (9:45)
Covariance and the Regression Line (15:08)
Exercises
FINISHED
Reading Stem and Leaf Plots*
Creating Bar Graphs 2*
Read Bar Graphs 1
Read Bar Graphs 2*
Creating Histograms
Reading Histograms
Calculating the Mean
Calculating the Median
Mean, Median and Mode*
Calculating the Mean: Data Displays
Calculating the Median: Data Displays
Effects of Shifting, Adding and Removing a Data Point
Missing Value Given the Mean
Median and Range Puzzlers
Shape of Distributions
Interpreting and Comparing Data Distributions*
Reading Box Plots*
Interpreting Quartiles
Sample and Population Variance*
Standard Deviation of a Population*
Sample and Population Standard Deviation*
Basic Set Notation*
Simple Probability*
Adding Probabilities*
Independent Probability*
Probabilities of Compound Events*
Dependent Probability*
Identifying Dependent and Independent Events*
Multiplying Dependent Probabilities*
Describing Subsets of Sample Spaces*
Constructing Probability Distributions*
Expected Value*
Expected Value with Empirical Probabilities
Expected Value with Calculated Probabilities
Making Decisions with Expected Values
DUE MONDAY, NOVEMBER 7 AT 4:30 PM
Constructing Scatter Plots*
Positive and Negative Linear Correlations from Scatter Plots
Interpreting slope and y-intercept of lines of best fit
Estimating equations of lines of best fit, and using them to make predictions
Making Good Scatter Plots
Positive and Negative Linear Correlations from Scatter Plots
Interpreting slope and y-intercept of lines of best fit
Estimating equations of lines of best fit, and using them to make predictions
Making Good Scatter Plots
Videos
Statistics Intro: Mean, Median and Mode (8:53)*
Finding Mean, Median and Mode (3:55)*
Exploring the Mean and Median (5:25)*
Comparing Means of Distributions (7:49)*
Means and Medians of Different Distributions (6:29)*
Inferring Population Mean from Sample Mean (10:02)*
Box and Whisker Plot (3:18)*
Constructing a Box and Whisker Plot (8:18)*
Finding the Range and Mid-range (2:03)*
Range, Variance and Standard Deviation as a Measures of Dispersion (12:34)*
Variance of a Population (8:05)*
Sample Variance (10:38)*
Review and Intuition Why We Divide by n-1 for the Unbiased Sample Variance (9:44)*
Simulation Showing Bias in Sample Variance (6:24)*
PROGRAM - Unbiased Estimation of Population Variance*
Another Simulation Giving Evidence that n-1 Gives Us an Unbiased Estimate of Variance (4:46)*
Simulation Providing Evidence that (n-1) Gives Us Unbiased Estimate (4:30)*
PROGRAM - Will It Converge Towards -1?*
Population Standard Deviation (8:05)*
Sample Standard Deviation and Bias (9:33)*
Statistics: Standard Deviation (13:07)*
Exploring Standard Deviation 1 Module (3:58)*
Statistics: Alternate Variance Formulas (12:17)*
Probability Explained (8:18)*
READING - Probability - The Basics*
Determining Probability (4:19)*
Describing Subsets of Sample Spaces Exercise (5:44)*
Finding Probability Example (2:56)*
Finding Probability Example 2 (9:56)*
Finding Probability Example 3 (2:11)*
Probability with Playing Cards and Venn Diagrams (10:02)*
Addition Rule for Probability (10:43)*
Compound Probability of Independent Events (6:00)*
Coin Flipping Probability (9:20)*
Die Rolling Probability (5:15)*
Free Throwing Probability (7:05)*
Three Pointer Vs. Free Throwing Probability (5:47)*
Probability without Equally Likely Events (8:58)*
Test Taking Probability and Independent Events (4:44)*
Die Rolling Probability with Independent Events (2:28)*
Dependent Probability Introduction (6:38)
Dependent Probability Example (9:01)
Dependent Probability Example 2 (6:34)
Independent or Dependent Probability Event? (2:39)
Analyzing Event Probability for Independence (6:48)
Analyzing Dependent Probability (9:30)
Calculating Conditional Probability (6:43)
Probability and the Monty Hall Problem (7:23)
Intersection and Union of Sets (7:44)
Relative Complement or Difference Between Sets (6:15)
Universal Set and Absolute Complement (6:26)
Subset, Strict Subset and Superset (4:32)
Bringing the Set Operations Together (6:28)
Random Variables (5:32)
Discrete and Continuous Random Variables (11:57)
Constructing a Probability Distribution for a Random Variable (6:48)
Probability Density Functions (10:02)
Term Life Insurance and Death Probability (4:22)
Getting Data from Expected Value (9:52)
Expected Profit from Lottery Ticket (9:18)
Expected Value While Fishing (8:24)
Comparing Insurance with Expected Value (9:16)
Law of Large Numbers (9:00)
Binomial Distribution (11:52)
Visualizing a Binomial Distribution (9:27)
Probability of Making 2 Shots in 6 Attempts (10:24)
Generalizing k Scores in n Events (4:13)
Free Throw Binomial Probability Distribution (8:39)
Graphing Basketball Binomial Distribution (4:23)
Expected Value of Binomial Distribution (16:56)
Poisson Process 1 (11:01)
Poisson Process 2 (12:42)
Studying, Shoe Size and Test Scores Scatter Plots (2:26)
People Smoking Less Over Time Scatter Plot (2:35)
Constructing a Scatter Plot (2:32)
Constructing Scatter Plot Exercise Example (1:58)
Comparing Models to Fit Data (4:05)
Correlation and Causality (10:45)
Fitting a Line to Data (7:48)
Estimating the Line of Best Fit Exercise (1:17)
Squared Error of Regression Line (6:47)
Proof (Part 1) Minimizing Squared Error to Regression Line (10:35)
Proof (Part 2) Minimizing Squared Error to Regression Line (9:54)
Proof (Part 3) Minimizing Squared Error to Regression Line (10:54)
Proof (Part 4) Minimizing Squared Error to Regression Line (4:18)
Regression Line Example (9:27)
Second Regression Example (9:15)
R-Squared or Coefficient of Determination (12:41)
Calculating R-Squared (9:45)
Covariance and the Regression Line (15:08)
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