Home » Mathematics » Statistics » Applications of the Sampling Distribution of the Sample Proportion

Section 1: Introduction
 Basic Ideas17:34
Section 2: Exploring Data
 Raw Data, Dotplots, Stemplots27:24
 Histograms, Cumulative Frequency Plots10:21
 Summarizing Distributions, Measuring Center16:04
 Measuring Spread: Range, IQR, Standard Deviation18:04
 Measuring Position: Quartiles, Percentiles, Standardized Scores16:28
 Boxplots15:37
 Comparing Distributions of Univariate Data24:19
 Exploring Bivariate Data: Scatterplots13:45
 Least Squares Regression17:32
 Exploring Categorical Data17:00
Section 3: Sampling and Experimentation
 Methods of Data Collection12:04
 Planning and Conducting Surveys13:51
 Planning and Conducting Experiments19:32
Section 4: Probability
 Experiment, Outcomes, and Sample Space14:54
 Calculating Probability14:13
 Probability and Events22:08
 Intersection of Events and the Multiplication Rule19:58
 Union of Events and the Addition Rule18:28
 Bayes' Rule16:59
Section 5: Discrete Random Variables and Probability Distribution
 Random Variables7:52
 Probability Distribution of a Discrete Random Variable15:55
 Mean and Standard Deviation of a Discrete Random Variable17:37
 Factorials, Combinations, Permutations15:43
 Binomial Probability Distribution21:38
 Poisson Probability Distribution13:40
 Geometric and Hypergeometric Probability Distributions19:08
 Combining Independent Random Variables20:26
Section 6: Continuous Random Variables and the Normal Distribution
 Continuous Probability Distribution6:19
 Normal Distribution6:42
 Standard Normal Distribution13:25
 Standardizing a Normal Distribution12:22
 Applications of the Normal Distribution12:20
 Finding Values When the Probability is Known12:44
Section 7: Sampling Distributions
 Population and Sampling Distributions12:02
 Mean, Standard Deviation, and the Shape of the Sampling Distribution of the Sampling Mean4:57
 Applications of the Sampling Distribution of the Sample Mean14:50
 Mean, Standard Deviation, and the Shape of the Sampling Distribution of the Sample Proportion3:58
 Applications of the Sampling Distribution of the Sample Proportion10:45
Section 8: Estimation of the Mean and Proportion
 Introduction to Estimation12:52
 Estimation of a Population Mean: Standard Deviation Known17:03
 Sample Size for Estimation of a Population Mean10:39
 Estimation of Population Mean: Sigma Not Known19:25
 Estimation of Population Proportion: Large Sample17:26
 Large Sample Confidence Intervals for Difference in Population Proportion16:16
 Confidence Intervals for a Difference in Means27:58
 Confidence Intervals for the Slope of a Least Squares Regression Line18:47
Section 9: Tests of Significance
 Introduction: Hypothesis Tests14:09
 Large Sample Test for a Proportion14:30
 Large Sample Test for a Difference in Two Proportions19:14
 Test for a Mean14:57
 Test for a Difference Between Two Means23:13
 Chi-Square Tests: One Way and Two Way24:33
 Hypothesis Testing for the Slope of a Least Squares Regression Line17:48

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Lecture Comments (1)

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Post by Sarawut Chaiyadech on September 6, 2013

you're funny and great!

Applications of the Sampling Distribution of the Sample Proportion

  • The sample proportion can be standardized (converted to a “z-score”) by subtracting p from and dividing the difference by ’s standard deviation.

  • Draw a picture of the curve and shade in the interval of which you want to find the probability.

Applications of the Sampling Distribution of the Sample Proportion

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Applications of the Sampling Distribution of the Sample Proportion

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Table of Contents

Section 1: Introduction
Basic Ideas

17m 34s

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

27m 24s

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
-1
Extra Example 2
-2
Histograms, Cumulative Frequency Plots

10m 21s

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

16m 4s

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
Extra Example 2
-2
Measuring Spread: Range, IQR, Standard Deviation

18m 4s

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
-1
Extra Example 2
-2
Measuring Position: Quartiles, Percentiles, Standardized Scores

16m 28s

Intro
0:00
Measure of Position
0:09
Quartile, Percentile, Z-Scores
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 (Z-Score)
8:27
Example: Standardized Score
9:23
Example: Standardized Score
10:21
Extra Example 1
-1
Extra Example 2
-2
Boxplots

15m 37s

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
-1
Extra Example 2
-2
Comparing Distributions of Univariate Data

24m 19s

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
-1
Extra Example 2
-2
Exploring Bivariate Data: Scatterplots

13m 45s

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
-1
Extra Example 2
-2
Least Squares Regression

17m 32s

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
-1
Extra Example 2
-2
Exploring Categorical Data

17m

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
-1
Extra Example 2
-2
Section 3: Sampling and Experimentation
Methods of Data Collection

12m 4s

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

13m 51s

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

19m 32s

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

14m 54s

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
-1
Extra Example 2
-2
Calculating Probability

14m 13s

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
Extra Example 2
-2
Probability and Events

22m 8s

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
Extra Example 2
-2
Intersection of Events and the Multiplication Rule

19m 58s

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
Extra Example 2
-2
Union of Events and the Addition Rule

18m 28s

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
-1
Extra Example 2
-2
Bayes' Rule

16m 59s

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
-1
Section 5: Discrete Random Variables and Probability Distribution
Random Variables

7m 52s

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
Probability Distribution of a Discrete Random Variable

15m 55s

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
Extra Example 2
-2
Mean and Standard Deviation of a Discrete Random Variable

17m 37s

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
-1
Extra Example 2
-2
Factorials, Combinations, Permutations

15m 43s

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
-1
Extra Example 2
-2
Binomial Probability Distribution

21m 38s

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
Extra Example 2
-2
Poisson Probability Distribution

13m 40s

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
Extra Example 2
-2
Geometric and Hypergeometric Probability Distributions

19m 8s

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
Extra Example 2
-2
Combining Independent Random Variables

20m 26s

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
-1
Extra Example 2
-2
Section 6: Continuous Random Variables and the Normal Distribution
Continuous Probability Distribution

6m 19s

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

6m 42s

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

13m 25s

Intro
0:00
Standard Normal Distribution
0:06
Z-Scores
1:08
Examples
1:57
More Examples
4:43
More Examples
7:12
Extra Example 1
-1
Extra Example 2
-2
Standardizing a Normal Distribution

12m 22s

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
Extra Example 2
-2
Applications of the Normal Distribution

12m 20s

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
Extra Example 2
-2
Finding Values When the Probability is Known

12m 44s

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
Extra Example 2
-2
Section 7: Sampling Distributions
Population and Sampling Distributions

12m 2s

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 Non-Sampling Error
6:00
Example
6:10
Non-Sampling 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

4m 57s

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

14m 50s

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
-1
Extra Example 2
-2
Mean, Standard Deviation, and the Shape of the Sampling Distribution of the Sample Proportion

3m 58s

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

10m 45s

Intro
0:00
Example 1: Retirement Plan
0:07
Example 2: Retirement Plan
3:04
Example 3: Voters
4:35
Extra Example 1
-1
Extra Example 2
-2
Section 8: Estimation of the Mean and Proportion
Introduction to Estimation

12m 52s

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

17m 3s

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
-1
Extra Example 2
-2
Sample Size for Estimation of a Population Mean

10m 39s

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
-1
Extra Example 2
-2
Estimation of Population Mean: Sigma Not Known

19m 25s

Intro
0:00
t-Distribution
0:10
Examples: t-Distribution
0:38
Using the t-Distribution
4:25
Confidence Interval
5:03
Example 1: Waiting Time
5:54
Example 2: MPG
9:35
Extra Example 1
-1
Extra Example 2
-2
Estimation of Population Proportion: Large Sample

17m 26s

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
-1
Extra Example 2
-2
Large Sample Confidence Intervals for Difference in Population Proportion

16m 16s

Intro
0:00
Sampling Distribution for Difference in Sample Proportion
0:08
Large and Independent Samples
0:11
Confidence Intervals for p1-p2
1:28
Example 1: Toothpaste
2:04
Example 2: Seat Belts
6:20
Extra Example 1
-1
Extra Example 2
-2
Confidence Intervals for a Difference in Means

27m 58s

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
-1
Extra Example 2
-2
Confidence Intervals for the Slope of a Least Squares Regression Line

18m 47s

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
-1
Extra Example 2
-2
Section 9: Tests of Significance
Introduction: Hypothesis Tests

14m 9s

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 Non-Rejection 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

14m 30s

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
-1
Extra Example 2
-2
Large Sample Test for a Difference in Two Proportions

19m 14s

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
-1
Extra Example 2
-2
Test for a Mean

14m 57s

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
t-Distribution Usage
6:24
Degrees of Freedom
6:53
Example 3: Height
7:01
Example 4: Sampling
9:50
Extra Example 1
-1
Extra Example 2
-2
Test for a Difference Between Two Means

23m 13s

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
Chi-Square Tests: One Way and Two Way

24m 33s

Intro
0:00
Goodness of Fit Test
0:07
Right-Tailed 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

17m 48s

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
-1
Extra Example 2
-2
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