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[eBook] [PDF] Intro Stats 6th Edition By Richard D. De Veaux_ Paul F. Velleman_ David E. Bock

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Pages: 846
File size: 53.09 MB
Format: Digital PDF
Course: Education
Category: eBook[PDF]

About this ebook

The Intro Stats (6th Edition) by Richard D. De Veaux, Paul F. Velleman, and David E. Bock covers introductory statistics topics structured across five primary parts: [1]

Part I: Exploring and Understanding Data

Stats Starts Here: Introduction to statistics, data, variables, and models. [1]
Displaying and Describing Data: Summarizing and visualizing categorical and quantitative variables, including shape, center, and spread. [1]
Relationships Between Categorical Variables: Contingency tables, conditional distributions, and three-way categorical tables. [1]
Understanding and Comparing Distributions: Graphical methods for comparing groups, identifying outliers, and an introduction to re-expressing data. [1]
The Standard Deviation as a Ruler and the Normal Model: Standardizing values (z-scores), shifting and scaling, normal models, normal percentiles, and normal probability plots. [1]

Part II: Exploring Relationships Between Variables

Scatterplots, Association, and Correlation: Visualizing and quantifying linear associations between two quantitative variables.
Linear Regression: Constructing and interpreting the least-squares regression line.
Regression Wisdom: Recognizing regression assumptions, diagnosing leveraging points, handling outliers, and identifying data quirks.
Multiple Regression: Expanding linear models to include multiple predictor variables. [1]

Part III: Gathering Data

Sample Surveys: Understanding populations, parameters, sampling frames, bias, and various sampling designs (SRS, stratified, cluster).
Experiments and Observational Studies: Designing randomized experiments, identifying factors and treatments, using blinding, and distinguishing them from observational studies. [1]

Part IV: From the Data at Hand to the World at Large

From Randomness to Probability: Foundations of randomness, sample spaces, and probability rules.
Sampling Distributions and Confidence Intervals for Proportions: The Central Limit Theorem for proportions, standard error, and creating one-proportion z-intervals.
Confidence Intervals for Means: Student's t-distribution, degrees of freedom, and creating one-sample t-intervals.
Testing Hypotheses: Mechanics of hypothesis testing, including null and alternative hypotheses, p-values, and one-sample z and t tests.
More About Tests and Intervals: Analyzing Type I and Type II errors, statistical power, and the relationship between confidence intervals and hypothesis tests. [1]

Part V: Inference for Relationships

Comparing Groups: Two-proportion z-tests/intervals and two-sample t-tests/intervals for independent groups.
Paired Samples and Blocks: Recognizing dependent data and conducting paired t-tests/intervals.
Comparing Counts: Chi-Square goodness-of-fit tests, tests of homogeneity, and tests of independence.
Inferences for Regression: Testing the slope of a population regression line and predicting values. [1]