by Ann E. Watkins, Richard L. Scheaffer and George W. Cobb

Edition: 04Copyright: 2004

Publisher: John Wiley & Sons, Inc.

Published: 2004

International: No

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1 A case study of statistics in action

1.1 Discrimination in the workplace : data exploration

1.2 Discrimination in the workplace : inference

2 Exploring distributions

2.1 The shapes of things : visualizing distributions

2.2 Graphical displays for distributions

2.3 Measures of center and spread

2.4 The normal distribution

3 Relationships between two quantitative variables

3.1 Scatterplots

3.2 Getting a line on the pattern

3.3 Correlation : the strength of a linear trend

3.4 Diagnostics : looking for features that the summaries miss

3.5 Shape-changing transformations

4 Sample surveys and experiments

4.1 Why take samples, and how not to

4.2 Randomizing : playing it safe by taking chances

4.3 Experiments and inference about cause

4.4 Designing experiments to reduce variability

5 Sampling distributions

5.1 Sampling from a population

5.2 Generating sampling distributions

5.3 Sampling distribution of the sample mean

5.4 Sampling distribution of the sample proportion

5.5 Sampling distribution of the sum and difference

6 Probability models

6.1 Sample spaces with equally likely outcomes

6.2 The addition rule and disjoint events

6.3 Conditional probability

6.4 Independent events

7 Probability distributions

7.1 Random variables and expected value

7.2 The binomial distribution

7.3 The geometric distribution

8 Inference for proportions

8.1 Estimating a proportion with confidence

8.2 Testing a proportion

8.3 A confidence interval for the difference of two proportions

8.4 A significance test for the difference of two proportions

9 Inference for means

9.1 Toward a confidence interval for a mean

9.2 Toward a significance test for a mean

9.3 When you estimate [sigma] : the t-distribution

9.4 The effect of long tails and outliers

9.5 Inference for the difference between two means

9.6 Paired comparisons

10 Chi-square tests

10.1 Testing a probability model : the chi-square goodness-of-fit test

10.2 The chi-square test of homogeneity

10.3 The chi-square test of independence

11 Inference for regression

11.1 Variation in the estimated slope

11.2 Making inferences about slopes

11.3 Transforming for a better fit

12 Statistics in action : case studies

12.1 Mum's the word!

12.2 Baseball : does money buy success?

12.3 Martin v. Westvaco revisited : testing for possible employment discrimination

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Table of Contents

1 A case study of statistics in action

1.1 Discrimination in the workplace : data exploration

1.2 Discrimination in the workplace : inference

2 Exploring distributions

2.1 The shapes of things : visualizing distributions

2.2 Graphical displays for distributions

2.3 Measures of center and spread

2.4 The normal distribution

3 Relationships between two quantitative variables

3.1 Scatterplots

3.2 Getting a line on the pattern

3.3 Correlation : the strength of a linear trend

3.4 Diagnostics : looking for features that the summaries miss

3.5 Shape-changing transformations

4 Sample surveys and experiments

4.1 Why take samples, and how not to

4.2 Randomizing : playing it safe by taking chances

4.3 Experiments and inference about cause

4.4 Designing experiments to reduce variability

5 Sampling distributions

5.1 Sampling from a population

5.2 Generating sampling distributions

5.3 Sampling distribution of the sample mean

5.4 Sampling distribution of the sample proportion

5.5 Sampling distribution of the sum and difference

6 Probability models

6.1 Sample spaces with equally likely outcomes

6.2 The addition rule and disjoint events

6.3 Conditional probability

6.4 Independent events

7 Probability distributions

7.1 Random variables and expected value

7.2 The binomial distribution

7.3 The geometric distribution

8 Inference for proportions

8.1 Estimating a proportion with confidence

8.2 Testing a proportion

8.3 A confidence interval for the difference of two proportions

8.4 A significance test for the difference of two proportions

9 Inference for means

9.1 Toward a confidence interval for a mean

9.2 Toward a significance test for a mean

9.3 When you estimate [sigma] : the t-distribution

9.4 The effect of long tails and outliers

9.5 Inference for the difference between two means

9.6 Paired comparisons

10 Chi-square tests

10.1 Testing a probability model : the chi-square goodness-of-fit test

10.2 The chi-square test of homogeneity

10.3 The chi-square test of independence

11 Inference for regression

11.1 Variation in the estimated slope

11.2 Making inferences about slopes

11.3 Transforming for a better fit

12 Statistics in action : case studies

12.1 Mum's the word!

12.2 Baseball : does money buy success?

12.3 Martin v. Westvaco revisited : testing for possible employment discrimination

Publisher Info

Publisher: John Wiley & Sons, Inc.

Published: 2004

International: No

Published: 2004

International: No

1.1 Discrimination in the workplace : data exploration

1.2 Discrimination in the workplace : inference

2 Exploring distributions

2.1 The shapes of things : visualizing distributions

2.2 Graphical displays for distributions

2.3 Measures of center and spread

2.4 The normal distribution

3 Relationships between two quantitative variables

3.1 Scatterplots

3.2 Getting a line on the pattern

3.3 Correlation : the strength of a linear trend

3.4 Diagnostics : looking for features that the summaries miss

3.5 Shape-changing transformations

4 Sample surveys and experiments

4.1 Why take samples, and how not to

4.2 Randomizing : playing it safe by taking chances

4.3 Experiments and inference about cause

4.4 Designing experiments to reduce variability

5 Sampling distributions

5.1 Sampling from a population

5.2 Generating sampling distributions

5.3 Sampling distribution of the sample mean

5.4 Sampling distribution of the sample proportion

5.5 Sampling distribution of the sum and difference

6 Probability models

6.1 Sample spaces with equally likely outcomes

6.2 The addition rule and disjoint events

6.3 Conditional probability

6.4 Independent events

7 Probability distributions

7.1 Random variables and expected value

7.2 The binomial distribution

7.3 The geometric distribution

8 Inference for proportions

8.1 Estimating a proportion with confidence

8.2 Testing a proportion

8.3 A confidence interval for the difference of two proportions

8.4 A significance test for the difference of two proportions

9 Inference for means

9.1 Toward a confidence interval for a mean

9.2 Toward a significance test for a mean

9.3 When you estimate [sigma] : the t-distribution

9.4 The effect of long tails and outliers

9.5 Inference for the difference between two means

9.6 Paired comparisons

10 Chi-square tests

10.1 Testing a probability model : the chi-square goodness-of-fit test

10.2 The chi-square test of homogeneity

10.3 The chi-square test of independence

11 Inference for regression

11.1 Variation in the estimated slope

11.2 Making inferences about slopes

11.3 Transforming for a better fit

12 Statistics in action : case studies

12.1 Mum's the word!

12.2 Baseball : does money buy success?

12.3 Martin v. Westvaco revisited : testing for possible employment discrimination