Название: OpenIntro Statistics: 4th EditionАвтор: David Diez, Mine Cetinkaya-Rundel, Christopher Barr
Издательство: OpenIntro, Inc.
Год: 2019
Формат: True PDF
Страниц: 422
Размер: 18.2 Mb
Язык: English
The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. Our inaugural effort is OpenIntro Statistics. Probability is optional, inference is key, and we feature real data whenever possible.
1. Introduction to data. Data structures, variables, and basic data collection techniques.
2. Summarizing data. Data summaries, graphics, and a teaser of inference using randomization.
3. Probability. Basic principles of probability.
4. Distributions of random variables. The normal model and other key distributions.
5. Foundations for inference. General ideas for statistical inference in the context of estimating the population proportion.
6. Inference for categorical data. Inference for proportions and tables using the normal and
chi-square distributions.
7. Inference for numerical data. Inference for one or two sample means using the t-distribution, statistical power for comparing two groups, and also comparisons of many means using ANOVA.
8. Introduction to linear regression. Regression for a numerical outcome with one predictor variable. Most of this chapter could be covered after Chapter 1.
9. Multiple and logistic regression. Regression for numerical and categorical data using many predictors.