Library · Mathematics

WorldClass Statistics

David M Diez, Mine Çetinkaya-Rundel, Christopher D Barr

First-year university · CC BY-SA 3.0 · read it here, in full

WorldClass Statistics is a derivative of OpenIntro Statistics, Fourth Edition, by David M Diez, Mine Çetinkaya-Rundel and Christopher D Barr, shared under a CC BY-SA 3.0 license, and is shared under the same license. The original book may be found at openintro.org/book/os.

1. Introduction to data

   1. Case study: using stents to prevent strokes
   2. Data basics
   3. Sampling principles and strategies
   4. Experiments
   5. Chapter 1 exercises

2. Summarizing data

   1. Examining numerical data
   2. Considering categorical data
   3. Case study: malaria vaccine
   4. Chapter 2 exercises

3. Probability

   1. Defining probability
   2. Conditional probability
   3. Sampling from a small population
   4. Random variables
   5. Continuous distributions
   6. Chapter 3 exercises

4. Distributions of random variables

   1. Normal distribution
   2. Geometric distribution
   3. Binomial distribution
   4. Negative binomial distribution
   5. Poisson distribution
   6. Chapter 4 exercises

5. Foundations for inference

   1. Point estimates and sampling variability
   2. Confidence intervals for a proportion
   3. Hypothesis testing for a proportion
   4. Chapter 5 exercises

6. Inference for categorical data

   1. Inference for a single proportion
   2. Difference of two proportions
   3. Testing for goodness of fit using chi-square
   4. Testing for independence in two-way tables
   5. Chapter 6 exercises

7. Inference for numerical data

   1. Paired data
   2. Difference of two means
   3. Power calculations for a difference of means
   4. Comparing many means with ANOVA
   5. Chapter 7 exercises

8. Introduction to linear regression

   1. Fitting a line, residuals, and correlation
   2. Least squares regression
   3. Types of outliers in linear regression
   4. Inference for linear regression
   5. Chapter 8 exercises

9. Multiple and logistic regression

   1. Introduction to multiple regression
   2. Model selection
   3. Checking model conditions using graphs
   4. Multiple regression case study: Mario Kart
   5. Introduction to logistic regression
   6. Chapter 9 exercises

10. Appendix: Exercise solutions

    1. Solutions: Introduction to data
    2. Solutions: Summarizing data
    3. Solutions: Probability
    4. Solutions: Distributions of random variables
    5. Solutions: Foundations for inference
    6. Solutions: Inference for categorical data
    7. Solutions: Inference for numerical data
    8. Solutions: Introduction to linear regression
    9. Solutions: Multiple and logistic regression

11. Appendix: Data sets within the text

    1. Introduction to data
    2. Summarizing data
    3. Probability
    4. Distributions of random variables
    5. Foundations for inference
    6. Inference for categorical data
    7. Inference for numerical data
    8. Introduction to linear regression
    9. Multiple and logistic regression

12. Appendix: Distribution tables

    1. Normal Probability Table
    2. t-Probability Table
    3. Chi-Square Probability Table

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