蜜桔直播

Chapter 2 - Organizing and Summarizing Data

2.2 Organizing Quantitative Data: The Popular Displays

 

Chapter 3 - Numerically Summarizing Data

3.1 Measures of Central Tendency

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  (note鈥�we consider data to have to have multiple modes if the data used most often "ties" with another data item)

3.2 Measures of Dispersion

• 
  Beth Dixon
• 
  Beth Dixon

3.4 Measures of Position and Outliers

• 
  Beth Dixon

3.5 The Five-Number Summary and Boxplots

 

Chapter 5 - Probability

5.1 Probability Rules

5.2 The Addition Rule and Complements

5.3 Independence and the Multiplication Rule

5.4 Conditional Probability and the General Multiplication Rule

5.5 Counting Techniques

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  *advanced

 

Chapter 7 鈥� The Normal Probability Distribution

7.2 The Standard Normal Distribution

• 
  Beth Dixon
• 
  Beth Dixon

7.3 Applications of the Normal Distribution

• 
  Beth Dixon

7.5 The Normal Approximation to the Binomial Probability Distribution

• *Only: Determine whether the normal distribution can be used to approximate the binomial distribution

 

Chapter 8 鈥� Sampling Distributions

8.1 Distribution of the Sample Mean

 

Chapter 9 鈥� Estimating the Value of a Parameter Using Confidence Intervals

9.2 Confidence Intervals for a Population Mean When the Population Standard Deviation is Unknown

9.3 Estimating a Population Proportion

• 
  Beth Dixon

 

Chapter 10 鈥� Hypothesis Tests Regarding a Parameter

10.1 The Language of Hypothesis Testing

10.2 Hypothesis Tests for a Population Mean-Population Standard Deviation Known

• * Only: Introduction of logic for hypothesis testing process for both classical and p-value methods (as needed for section 10.3)

10.3 Hypothesis Tests for a Population Mean-Population Standard Deviation

• 
  Beth Dixon