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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
Ann E. Watkins, Richard L. Scheaffer and George W. Cobb
ISBN13: 978-0470413296Table 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