Książki

This version includes both the textbook and LaunchPad Access.
Introduction to the Practice of Statistics shows students how to produce and interpret data from real-world contexts, guiding them through the same type of data gathering and analysis that working statisticians do every day. With this phenomenally successful approach originally developed by David Moore and George McCabe, statistics is more than just a collection of techniques and formulas. Instead, students develop a systematic way of thinking about data, with a focus on problem-solving that helps them understand statistical concepts and master statistical reasoning. With the LaunchPad version of the textbook, both the print and online resource are combined, putting powerful statistical tools and interactive learning features in students' hands.

Introduction to the Practice of Statistics plus LaunchPad (AUS Pack)

1.1 Data.- 1.2 Displaying Distributions with Graphs.- 1.3 Describing Distributions with Numbers.- 1.4 Density Curves and Normal Distributions.- 2.1 Relationships.- 2.2 Scatterplots.- 2.3 Correlation.- 2.4 Least-Squares Regression.- 2.5 Cautions about Correlation and Regression.- <2.6 Data Analysis for Two-Way Tables.- 2.7 The Question of Causation.- 3.1 Sources of Data.- 3.2 Design of Experiments.- 3.3 Sampling Design.- 3.4 Ethics.- 4.1 Randomness.- 4.2 Probability Models.- 4.3 Random Variables.- 4.4 Means and Variances of Random Variables.- 4.5 General Probability Rules.- 5.1 Toward Statistical Inference.- 5.2 The Sampling Distribution of a Sample Mean.- 5.3 Sampling Distributions for Counts and Proportions.- 6.1 Estimating with Confidence.- 6.2 Tests of Significance.- 6.3 Use and Abuse of Tests.- 6.4 Power and Inference as a Decision Power.- 7.1 Inference for the Mean of a Population.- 7.2 Comparing Two Means.- 7.3 Additional Topics on Inference.- 8.1 Inference for a Single Proportion.- 8.2 Comparing Two Proportions.- 9.1 Inference for Two-Way Tables.- 10.1 Simple Linear Regression.- 10.2 More Detail about Simple Linear Regression.- 11.1 Inference for Multiple Regression.- 11.2 A Case Study.- 12.1 Inference for One-Way Analysis of Variance.- 12.2 Comparing the Means.- 13.1 The Two-Way ANOVA Model.- 14.1 The Logistic Regression Model.- 14.2 Inference for Logistic Regression.- 15.1 The Wilcoxon Rank Sum Test.- 15.2 The Wilcoxon Signed Rank Test.- 15.3 The Kruskal-Wallis Test.- 16.1 The Bootstrap Idea.- 16.2 First Steps in Using the Bootstrap.- 16.3 How Accurate Is a Bootstrap Distribution?.- 16.4 Bootstrap Confidence Intervals.- 16.5 Significance Testing Using Permutation Tests.- 17.1 Processes and Statistical Process Control.- 17.2 Using Control Charts.- 17.3 Process Capability Indexes.- 17.4 Control Charts for Sample Proportions.-