Section 1: Introduction 

Basic Ideas 
17:34 
 
Intro 
0:00  
 
Basic Definitions 
0:09  
 
 Element (member, unit) 
0:20  
 
 Variable 
1:01  
 
 Observation (measurement) 
1:18  
 
 Data Set 
1:40  
 
Example: Basic Definitions 
1:55  
 
Qualitative Variables 
4:58  
 
Quantitative Variables 
6:16  
 
 Discrete Variable 
6:33  
 
 Continuous Variable 
7:36  
 
Cross Section vs Time Series Data 
8:58  
 
Summation Notation 
10:50  
 
Summation Notation 2 
12:59  
 
Summation Notation 3 
15:32  
Section 2: Exploring Data 

Raw Data, Dotplots, Stemplots 
27:24 
 
Intro 
0:00  
 
Raw Data 
0:07  
 
 Ungrouped Data 
0:25  
 
 Example: Ages 
0:39  
 
Features of Graphical Displays of Distributions 
1:28  
 
 Center and Spread 
1:54  
 
 Clusters and Gaps 
2:04  
 
 Outliers (extreme values) 
2:12  
 
 Symmetric 
2:48  
 
 Skewed 
3:14  
 
 Uniform 
3:47  
 
Dotplots 
4:58  
 
Example: Dotplots 
8:51  
 
Stemplot 
11:12  
 
 Stem and Leaf 
11:17  
 
Example: Stemplot 
15:18  
 
Extra Example 1 
3:48  
 
Extra Example 2 
4:00  

Histograms, Cumulative Frequency Plots 
10:21 
 
Intro 
0:00  
 
Features of Graphical Displays of Distributions 
0:07  
 
Histogram 
3:03  
 
 Common Programs 
3:09  
 
Example: Histogram 
6:14  
 
Cumulative Frequency Plot 
7:43  
 
Example: Cumulative Frequency Plot 
8:16  

Summarizing Distributions, Measuring Center 
16:04 
 
Intro 
0:00  
 
Measures of Central Tendency 
0:08  
 
Mean (average) 
0:28  
 
 Mean for Population Data 
0:51  
 
 Mean for Sample Data 
1:18  
 
Example: Mean 
1:57  
 
Example: Mean 
2:49  
 
Median 
3:53  
 
Example: Median 
4:52  
 
Example: Median 
6:47  
 
Mode 
8:01  
 
 Unimodal 
8:11  
 
 Bimodal 
8:19  
 
 Multimodal 
8:24  
 
Example: Mode 
8:34  
 
Example: Mode 
9:53  
 
Effect of Changing Units 
10:31  
 
Extra Example 1 
1:53  
 
Extra Example 2 
1:36  

Measuring Spread: Range, IQR, Standard Deviation 
18:04 
 
Intro 
0:00  
 
Measuring Spread 
0:08  
 
Range 
1:06  
 
 Example 
1:16  
 
 Example 
1:35  
 
Standard Deviation 
2:05  
 
 Population Standard Deviation 
2:14  
 
 Sample Standard Deviation 
3:13  
 
Example: Standard Deviation 
4:11  
 
Example: Standard Deviation 
6:05  
 
Interquartile Range (IQR) 
8:05  
 
Example: Interquartile Range 
9:03  
 
Example: Interquartile Range 
10:27  
 
Extra Example 1 
3:15  
 
Extra Example 2 
2:28  

Measuring Position: Quartiles, Percentiles, Standardized Scores 
16:28 
 
Intro 
0:00  
 
Measure of Position 
0:09  
 
 Quartile, Percentile, ZScores 
0:24  
 
Quartiles (Q1, Q2, Q3) 
0:32  
 
 Example 
0:51  
 
Example: Quartiles 
1:28  
 
Example: Quartiles 
3:27  
 
Percentiles 
5:44  
 
Example: Percentiles 
6:19  
 
Example: Percentiles 
7:24  
 
Standardized Score (ZScore) 
8:27  
 
Example: Standardized Score 
9:23  
 
Example: Standardized Score 
10:21  
 
Extra Example 1 
2:56  
 
Extra Example 2 
2:11  

Boxplots 
15:37 
 
Intro 
0:00  
 
What is a Boxplot? 
0:05  
 
 Five Number Summary 
0:15  
 
Example: Boxplot 
0:30  
 
Example: Boxplot 
4:33  
 
Extra Example 1 
3:09  
 
Extra Example 2 
2:21  

Comparing Distributions of Univariate Data 
24:19 
 
Intro 
0:00  
 
Comparing Features 
0:07  
 
 Compare Center & Spread 
0:11  
 
 Compare Clusters & Gaps 
0:23  
 
 Compare Outliers and Unusual Features 
0:33  
 
 Compare Shapes 
0:55  
 
 Symmetric 
1:00  
 
 Skewed Right 
1:20  
 
 Skewed Left 
1:31  
 
 Uniform 
1:41  
 
Example: Dotplots 
1:56  
 
Example: Back to Back Stemplots 
5:16  
 
Example: Parallel Boxplots 
10:21  
 
Example: Back to Back Stemplots 
15:03  
 
Extra Example 1 
2:00  
 
Extra Example 2 
5:06  

Exploring Bivariate Data: Scatterplots 
13:45 
 
Intro 
0:00  
 
Bivariate Data 
0:08  
 
 Example: Student Scores 
0:31  
 
Example: Scatterplot 
1:08  
 
Example: Scatterplot 
2:36  
 
Correlation and Linearity 
3:49  
 
Example: Correlation 
5:30  
 
Example: Correlation 
6:55  
 
Extra Example 1 
3:10  
 
Extra Example 2 
2:21  

Least Squares Regression 
17:32 
 
Intro 
0:00  
 
Least Squares Regression Line 
0:06  
 
 Why Least Squares? 
0:25  
 
 Equations 
1:21  
 
Example 1: Age and Price 
2:02  
 
Example 2: Weld Diameter 
5:47  
 
Diagnostics 
8:39  
 
 Residuals 
8:58  
 
 Normal Probability Plot 
10:09  
 
 Studentized Residuals (Hat Matrix) 
10:29  
 
Transformations 
10:48  
 
 Logarithmic Transformation 
11:04  
 
 Square Root Transformation 
11:44  
 
Extra Example 1 
3:07  
 
Extra Example 2 
2:11  

Exploring Categorical Data 
17:00 
 
Intro 
0:00  
 
Frequency Tables 
0:05  
 
 Example: Student Age 
0:16  
 
 Relative Frequency 
0:55  
 
Bar Graphs 
1:59  
 
Marginal and Joint Probabilities 
3:54  
 
Example 1: Gender and Beer 
6:52  
 
Conditional Probabilities 
8:47  
 
Example 2: Gender and Beer 
11:41  
 
Extra Example 1 
2:09  
 
Extra Example 2 
1:56  
Section 3: Sampling and Experimentation 

Methods of Data Collection 
12:04 
 
Intro 
0:00  
 
Purpose 
0:05  
 
Census 
1:22  
 
 Example: US Census 
1:36  
 
 Example: Fireworks Factory 
2:34  
 
Sample Survey 
3:41  
 
Experiment 
6:12  
 
 Example: Coke vs Pepsi 
7:09  
 
Observational Study 
8:19  
 
Observational or Experiment 
9:30  
 
 Example 1 
9:53  
 
 Example 2 
10:24  
 
 Example 3 
11:17  

Planning and Conducting Surveys 
13:51 
 
Intro 
0:00  
 
Ideal Surveys 
0:06  
 
 Random Selection 
0:16  
 
Characteristics of Surveys 
0:42  
 
 Chance 
0:50  
 
 Random Samples 
1:02  
 
 No Source of Bias 
1:32  
 
Populations, Samples, Random Selection 
2:21  
 
 Population 
2:28  
 
 Sample 
2:51  
 
Sources of Bias 
4:14  
 
 Example 
4:33  
 
Sampling Methods 
7:27  
 
 Simple Random Sampling (SRS) 
7:40  
 
 Example 
8:33  
 
 Stratified Random Sampling (Strata) 
10:03  
 
 Example 
11:06  
 
 Cluster Sampling 
12:19  
 
 Example 
13:06  

Planning and Conducting Experiments 
19:32 
 
Intro 
0:00  
 
Purpose 
0:06  
 
Characteristics 
1:00  
 
Basic Terms 
2:00  
 
 Treatment 
2:12  
 
 Control Group 
2:30  
 
 Experimental Units 
3:17  
 
 Random Assignment 
3:38  
 
 Replication 
4:19  
 
Sources of Bias and Confounding 
4:48  
 
 Counfounding 
5:00  
 
 Example 
5:29  
 
 Placebo Effect 
6:41  
 
 Example 
7:08  
 
 Blinding 
7:56  
 
 Example 
8:24  
 
Completely Randomized Design 
9:12  
 
Randomized Block Design 
12:44  
 
 Block 
12:55  
 
 Matched Pairs 
13:22  
 
 Example 
13:41  
 
 Randomized Block Design 
15:09  
 
 Example 
15:30  
 
Studies and Surveys vs Experiments 
17:03  
Section 4: Probability 

Experiment, Outcomes, and Sample Space 
14:54 
 
Intro 
0:00  
 
Basic Definitions 
0:29  
 
 Experiment 
0:35  
 
 Outcomes 
0:55  
 
 Sample Space 
1:04  
 
Examples 
1:34  
 
 Roll a Die 
1:39  
 
 Flip a Coin 
2:33  
 
Simple and Compound Events 
3:30  
 
 Event 
3:43  
 
 Simple Event 
3:58  
 
 Compound Event 
4:27  
 
Example 
5:14  
 
Extra Example 1 
0:59  
 
Extra Example 2 
4:21  

Calculating Probability 
14:13 
 
Intro 
0:00  
 
What is Probability 
0:27  
 
 Range 
0:53  
 
 Sum of Probabilities 
1:26  
 
 Example: Football Game 
2:05  
 
Classical Probability 
2:53  
 
 Equally Likely Outcomes 
3:05  
 
 Example: Coin Flip 
4:08  
 
 Example: Die Roll 
5:12  
 
Relative Frequency 
6:44  
 
 Example 
7:22  
 
Subjective Probability 
9:38  
 
 Example 
10:06  
 
Extra Example 1 
1:04  
 
Extra Example 2 
1:33  

Probability and Events 
22:08 
 
Intro 
0:00  
 
Mutually Exclusive Events 
0:17  
 
 Example: Coin Flip 
0:27  
 
 Example: Die Roll 
3:03  
 
Independent Events 
5:13  
 
 Notation 
3:31  
 
 Example: Coin 
6:01  
 
Independent Events, cont. 
9:19  
 
 Example: Coffee Drinkers 
9:23  
 
Mutually Exclusive vs Independent 
13:03  
 
Complementary Events 
14:08  
 
 Example: Coffee Drinkers 
15:37  
 
Extra Example 1 
1:16  
 
Extra Example 2 
3:32  

Intersection of Events and the Multiplication Rule 
19:58 
 
Intro 
0:00  
 
Intersection of Events 
0:08  
 
 Venn Diagram 
1:20  
 
Multiplication Rule 
2:22  
 
 Joint Probability 
2:23  
 
 Example 
3:23  
 
Example 
6:30  
 
Multiplication Rule for Independent Events 
10:30  
 
 Example 
11:39  
 
Joint Probability of Mutually Exclusive Events 
15:24  
 
Extra Example 1 
1:24  
 
Extra Example 2 
2:09  

Union of Events and the Addition Rule 
18:28 
 
Intro 
0:00  
 
Union of Events 
0:06  
 
 Venn Diagram 
0:52  
 
Addition Rule 
2:01  
 
 Example: Coffee Drinkers 
3:25  
 
Example 
6:26  
 
Addition Rule for Mutually Exclusive Events 
9:11  
 
Example 
10:27  
 
Extra Example 1 
2:41  
 
Extra Example 2 
1:15  

Bayes' Rule 
16:59 
 
Intro 
0:00  
 
Partition of Events 
0:07  
 
 Venn Diagram 
0:17  
 
Law of Total Probability 
3:12  
 
Bayes' Rule 
6:11  
 
Example 
9:09  
 
Extra Example 1 
4:07  
Section 5: Discrete Random Variables and Probability Distribution 

Random Variables 
7:52 
 
Intro 
0:00  
 
Definition 
0:06  
 
 Example 
0:24  
 
Discrete Random Variables 
1:22  
 
 Example 
1:56  
 
Continuous Random Variable 
3:53  
 
 Example 
4:12  
 
Extra Example 1 
1:51  

Probability Distribution of a Discrete Random Variable 
15:55 
 
Intro 
0:00  
 
Definition 
0:09  
 
 Example 
0:24  
 
Rules of a Probability Distribution 
3:27  
 
 Rule 1 
3:33  
 
 Rule 2 
4:30  
 
 Example 1 
4:59  
 
 Example 2 
6:00  
 
 Example 3 
6:38  
 
Example: Defective DVDs 
7:19  
 
Extra Example 1 
1:56  
 
Extra Example 2 
1:28  

Mean and Standard Deviation of a Discrete Random Variable 
17:37 
 
Intro 
0:00  
 
Mean of a Discrete Random Variable 
0:10  
 
 Example 
1:17  
 
Example: Numbers Game 
3:09  
 
Standard Deviation of a Discrete Random Variable 
6:02  
 
 Example 
7:46  
 
Example: Cars in a Town 
10:12  
 
Extra Example 1 
2:24  
 
Extra Example 2 
2:22  

Factorials, Combinations, Permutations 
15:43 
 
Intro 
0:00  
 
Counting Rule 
0:08  
 
 Example: Coin Toss 
0:56  
 
 Example: Football Team 
1:45  
 
Factorials 
2:54  
 
 Example 
3:39  
 
 Zero Factorial 
4:03  
 
 Example 
4:20  
 
Combinations 
5:16  
 
 Example 
6:23  
 
Permutations 
8:16  
 
 Example 
9:01  
 
Extra Example 1 
2:58  
 
Extra Example 2 
2:20  

Binomial Probability Distribution 
21:38 
 
Intro 
0:00  
 
Binomial Experiment 
0:07  
 
 Discrete Random Variable 
0:34  
 
 Trial 
1:01  
 
 Bernoulli Trials 
1:26  
 
Example: Roll Die 
2:37  
 
Binomial Probability Distribution 
4:36  
 
Example: Winter Holiday Stress 
6:58  
 
Example: MRI 
9:51  
 
Probability of Success and Shape 
12:42  
 
 Symmetric 
12:54  
 
 Skewed Right 
13:23  
 
 Skewed Left 
14:13  
 
Mean/Standard Deviation of Binomial Distribution 
15:03  
 
 Example: Stress 
16:06  
 
 Example: MRI 
17:07  
 
Extra Example 1 
1:47  
 
Extra Example 2 
1:49  

Poisson Probability Distribution 
13:40 
 
Intro 
0:00  
 
Poisson Probability Distribution 
0:06  
 
 Conditions 
0:43  
 
Example: Complaints 
3:18  
 
Example: Failed Businesses 
5:01  
 
Mean/Standard Deviation of Poisson Distribution 
7:52  
 
 Example: Complaints 
8:53  
 
 Example: Failed Businesses 
9:46  
 
Extra Example 1 
1:19  
 
Extra Example 2 
1:48  

Geometric and Hypergeometric Probability Distributions 
19:08 
 
Intro 
0:00  
 
Geometric Probability Distribution 
0:08  
 
Example: Engine Malfunction 
3:00  
 
Example: Interviews 
5:45  
 
Hypergeometric Probability Distribution 
7:36  
 
Example: Engineers 
10:16  
 
Example: Marbles 
12:55  
 
Extra Example 1 
1:14  
 
Extra Example 2 
2:00  

Combining Independent Random Variables 
20:26 
 
Intro 
0:00  
 
Independence vs Dependence 
0:09  
 
Mean of Sums for Independent Random Variables 
2:32  
 
Example 
4:02  
 
Example 
5:58  
 
Variance for Sums of Independent Random Variables 
8:49  
 
Example 
10:30  
 
Example 
12:26  
 
Extra Example 1 
3:04  
 
Extra Example 2 
1:59  
Section 6: Continuous Random Variables and the Normal Distribution 

Continuous Probability Distribution 
6:19 
 
Intro 
0:00  
 
Continuous Random Variable 
0:07  
 
Probability Density Function 
0:54  
 
More About Densities 
3:07  
 
More About Densities, cont. 
4:06  

Normal Distribution 
6:42 
 
Intro 
0:00  
 
Normal Distribution 
0:05  
 
 Bell Shaped Curve 
0:09  
 
Properties of the Normal Distribution 
1:02  
 
 Area Under the Curve (Density Curve) 
1:07  
 
Symmetric About the Mean 
1:40  
 
Two Tails 
2:21  
 
Normal Distribution 
3:07  
 
 Different Means 
3:10  
 
Different Standard Deviations 
4:32  

Standard Normal Distribution 
13:25 
 
Intro 
0:00  
 
Standard Normal Distribution 
0:06  
 
 ZScores 
1:08  
 
Examples 
1:57  
 
More Examples 
4:43  
 
More Examples 
7:12  
 
Extra Example 1 
1:51  
 
Extra Example 2 
1:33  

Standardizing a Normal Distribution 
12:22 
 
Intro 
0:00  
 
Standardizing a Normal Distribution 
0:07  
 
 Mean and Standard Deviation of X 
1:13  
 
Examples 
1:39  
 
More Examples 
3:22  
 
More Examples 
6:17  
 
Extra Example 1 
1:55  
 
Extra Example 2 
1:12  

Applications of the Normal Distribution 
12:20 
 
Intro 
0:00  
 
Standardizing a Normal Distribution 
0:08  
 
Example: US Debt 
0:59  
 
Example: Toy Assembly 
3:19  
 
Example: Soda 
5:04  
 
Example: Calculator 
7:27  
 
Extra Example 1 
1:31  
 
Extra Example 2 
1:45  

Finding Values When the Probability is Known 
12:44 
 
Intro 
0:00  
 
Example 1 
0:10  
 
Example 2 
1:32  
 
Example 3 
3:12  
 
Example 4: Battery Life 
4:18  
 
Example 5: SAT Scores 
6:33  
 
Extra Example 1 
1:24  
 
Extra Example 2 
2:21  
Section 7: Sampling Distributions 

Population and Sampling Distributions 
12:02 
 
Intro 
0:00  
 
Population Distribution 
0:06  
 
 Example: Teaching Experience 
0:14  
 
Sampling Distribution 
1:31  
 
Example: Teaching Experience 
2:16  
 
Sampling Error 
5:29  
 
 Random and No NonSampling Error 
6:00  
 
 Example 
6:10  
 
NonSampling Error 
7:22  
 
 Example 
7:38  
 
Example: Six Numbers 
9:17  

Mean, Standard Deviation, and the Shape of the Sampling Distribution of the Sampling Mean 
4:57 
 
Intro 
0:00  
 
Mean/Standard Deviation of Sample Mean 
0:10  
 
 Estimator 
0:57  
 
 Unbiased Estimator 
1:15  
 
Sampling Distribution of Sample Mean 
1:50  
 
 Spread 
1:53  
 
 Standard Deviation 
2:18  
 
 Consistent Estimator 
2:40  
 
Shape of Sampling Distribution 
2:51  
 
 Normal 
3:21  
 
Shape of Sampling Distribution, cont. 
3:50  
 
 Central Limit Theorem 
4:15  

Applications of the Sampling Distribution of the Sample Mean 
14:50 
 
Intro 
0:00  
 
Example 1: Speed Limit 
0:08  
 
Example 2: Speed Limit 
2:50  
 
Example 3: Speed Limit 
4:20  
 
Example 4: Study Times 
6:20  
 
Example 5: Study Times 
9:02  
 
Extra Example 1 
2:14  
 
Extra Example 2 
2:12  

Mean, Standard Deviation, and the Shape of the Sampling Distribution of the Sample Proportion 
3:58 
 
Intro 
0:00  
 
Population vs Sample Proportions 
0:10  
 
 Population Proportion 
0:16  
 
 Sample Proportion 
0:23  
 
 Sample: Eye Color 
0:36  
 
Mean/Standard Deviation of Sample Proportion 
1:47  
 
 Mean 
1:51  
 
 Unbiased Estimator 
2:07  
 
 Standard Deviation 
2:28  
 
Shape of the Distribution 
3:07  

Applications of the Sampling Distribution of the Sample Proportion 
10:45 
 
Intro 
0:00  
 
Example 1: Retirement Plan 
0:07  
 
Example 2: Retirement Plan 
3:04  
 
Example 3: Voters 
4:35  
 
Extra Example 1 
2:27  
 
Extra Example 2 
1:40  
Section 8: Estimation of the Mean and Proportion 

Introduction to Estimation 
12:52 
 
Intro 
0:00  
 
Estimation 
0:06  
 
 Parameter 
0:29  
 
 Estimate 
1:02  
 
 Estimator 
1:10  
 
 Example 
1:20  
 
Steps for Estimation 
2:21  
 
 Example: Dartboard 
3:08  
 
 Consistent/Bias 
3:41  
 
 Inconsistent/Unbiased 
4:09  
 
 Consistent/Unbiased 
4:44  
 
Point Estimate 
5:33  
 
 Example 
5:50  
 
Interval Estimate 
6:35  
 
 Margin of Error 
7:15  
 
Confidence Interval 
7:35  
 
 Confidence Level 
7:55  
 
Example 
8:10  
 
More on Confidence Intervals 
10:18  
 
 Confidence Level Increase 
11:41  
 
 Sample Size Increase 
12:25  

Estimation of a Population Mean: Standard Deviation Known 
17:03 
 
Intro 
0:00  
 
Population is Normal, n<30 
0:10  
 
 Confidence Interval 
0:28  
 
Example 1 
2:34  
 
Example 2 
5:54  
 
When n>30, Any Distribution 
7:58  
 
 Confidence Interval 
8:48  
 
Example 3 
9:14  
 
Example 4 
11:16  
 
Extra Example 1 
2:24  
 
Extra Example 2 
1:34  

Sample Size for Estimation of a Population Mean 
10:39 
 
Intro 
0:00  
 
Determining Sample Size 
0:07  
 
 Finding n 
0:30  
 
 Origin of Equation 
0:56  
 
Example 1 
2:16  
 
Example 2 
4:42  
 
Extra Example 1 
2:13  
 
Extra Example 2 
1:43  

Estimation of Population Mean: Sigma Not Known 
19:25 
 
Intro 
0:00  
 
tDistribution 
0:10  
 
Examples: tDistribution 
0:38  
 
Using the tDistribution 
4:25  
 
 Confidence Interval 
5:03  
 
Example 1: Waiting Time 
5:54  
 
Example 2: MPG 
9:35  
 
Extra Example 1 
3:23  
 
Extra Example 2 
2:54  

Estimation of Population Proportion: Large Sample 
17:26 
 
Intro 
0:00  
 
Population vs Sample Proportion 
0:10  
 
Confidence Intervals for p 
1:50  
 
Example 1: Credit 
2:18  
 
Example 2: Time 
4:59  
 
Sample Size for the Estimation of p 
7:31  
 
 Margin of Error 
7:55  
 
 Conservative Estimate 
8:17  
 
Example 3: Gambling 
8:40  
 
Example 4: Clocks 
10:53  
 
Extra Example 1 
2:32  
 
Extra Example 2 
1:50  

Large Sample Confidence Intervals for Difference in Population Proportion 
16:16 
 
Intro 
0:00  
 
Sampling Distribution for Difference in Sample Proportion 
0:08  
 
 Large and Independent Samples 
0:11  
 
 Confidence Intervals for p1p2 
1:28  
 
Example 1: Toothpaste 
2:04  
 
Example 2: Seat Belts 
6:20  
 
Extra Example 1 
3:32  
 
Extra Example 2 
2:50  

Confidence Intervals for a Difference in Means 
27:58 
 
Intro 
0:00  
 
Independent Samples: Standard Deviations Known 
0:07  
 
Confidence Interval for Difference of Means 
1:12  
 
Example 1: Starting Salary 
1:35  
 
Example 2: Fill 
5:36  
 
Independent Samples: Standard Deviations Not Known 
7:54  
 
Pooled Standard Deviation for Two Samples 
8:46  
 
Confidence Interval for Difference of Means 
9:32  
 
Example 3: Caffeine 
10:35  
 
Example 4: Test Scores 
15:20  
 
Inference about Difference of Means for Paired Samples 
19:05  
 
 Paired or Matched Sample 
19:21  
 
Inference about Difference of Means for Paired Samples 
20:58  
 
Extra Example 1 
3:40  
 
Extra Example 2 
2:03  

Confidence Intervals for the Slope of a Least Squares Regression Line 
18:47 
 
Intro 
0:00  
 
Sampling Distribution of b 
0:08  
 
Calculating the Estimator of Standard Deviation of b 
1:03  
 
Confidence Interval for Beta 
1:31  
 
Example 1: Age and Price 
2:24  
 
Example 2: Weld Diameter 
6:41  
 
Extra Example 1 
4:27  
 
Extra Example 2 
3:37  
Section 9: Tests of Significance 

Introduction: Hypothesis Tests 
14:09 
 
Intro 
0:00  
 
Two Hypotheses 
0:13  
 
 Null Hypothesis 
0:21  
 
 Alternative Hypothesis 
0:36  
 
 Example 
1:05  
 
Example: Two Hypotheses 
1:43  
 
Rejection and NonRejection Regions 
3:25  
 
Type 1 and Type 2 Errors 
5:30  
 
 Type 1 Error 
6:44  
 
 Significance Level 
7:08  
 
 Type 2 Error 
7:42  
 
 Power of the Test 
8:30  
 
Tails of the Test 
9:29  

Large Sample Test for a Proportion 
14:30 
 
Intro 
0:00  
 
Test Statistic Z 
0:08  
 
 Why Z? 
0:29  
 
Example 1: TV Violence 
1:10  
 
Example 2: Smoking 
5:16  
 
Extra Example 1 
3:25  
 
Extra Example 2 
2:52  

Large Sample Test for a Difference in Two Proportions 
19:14 
 
Intro 
0:00  
 
Pooled Estimate of P1 and P2 
0:09  
 
Example 1: Softball Bases 
1:34  
 
Example 2: Sleep Problems 
6:59  
 
Extra Example 1 
4:11  
 
Extra Example 2 
4:12  

Test for a Mean 
14:57 
 
Intro 
0:00  
 
Standard Deviation is Known 
0:07  
 
 Central Limit Theory for n>30 
0:32  
 
Example 1: Cheese Weight 
0:53  
 
Example 2: Observations 
3:53  
 
Standard Deviation Not Known 
6:15  
 
 tDistribution Usage 
6:24  
 
 Degrees of Freedom 
6:53  
 
Example 3: Height 
7:01  
 
Example 4: Sampling 
9:50  
 
Extra Example 1 
2:02  
 
Extra Example 2 
1:32  

Test for a Difference Between Two Means 
23:13 
 
Intro 
0:00  
 
Standard Deviation Known, Unpaired 
0:08  
 
Example 1: Boredom 
1:17  
 
Example 2: Smoking 
4:15  
 
Population Standard Deviations Unknown, But Equal 
7:10  
 
 Pooled Standard Deviation for Two Samples 
7:49  
 
Example 3: Diet Soda 
8:28  
 
Example 4: TV 
12:12  
 
Paired Samples 
15:50  
 
Example 5: Hormone Level 
16:33  
 
Example 6: Hypnotism 
19:43  

ChiSquare Tests: One Way and Two Way 
24:33 
 
Intro 
0:00  
 
Goodness of Fit Test 
0:07  
 
 RightTailed Test 
0:52  
 
Example 1: Die Rolls 
1:16  
 
Example 2: Stolen Vehicles 
3:31  
 
Test of Independence 
7:02  
 
Example 3: Debt 
7:51  
 
Example 4: Contraceptive Use 
13:14  
 
Test of Homogeneity 
16:31  
 
Example 5: New Product 
17:09  
 
Example 6: Oil 
21:24  

Hypothesis Testing for the Slope of a Least Squares Regression Line 
17:48 
 
Intro 
0:00  
 
Sampling Distribution of b 
0:08  
 
Calculating the Estimator of Standard Deviation of b 
1:18  
 
Hypothesis Testing for Beta 
1:50  
 
Example 1: Age 
2:25  
 
Example 2: Weld Diameter 
6:42  
 
Extra Example 1 
3:30  
 
Extra Example 2 
3:10  