Chapter 11 Statistics

Learning Objectives

After completing this chapter, you will be able to:

  • Compute probabilities, quantiles, and random samples from the normal distribution
  • Work with other common distributions (t, chi-squared, uniform, binomial, Poisson)
  • Generate random permutations and samples using sample()
  • Simulate and visualize multivariate normal data

In this chapter, you will dive into the world of statistics. As a language initially designed for statistical computing, R undoubtedly provides a wide range of functions related to all aspects of probability and statistics. You will start with functions related to normal distribution in Section 11.1.

At a glance – Chapter ROADMAP

Section 11.1. Normal Distribution: Work with PDF, CDF, quantiles, and random generation.
Section 11.2. Other Distributions: Explore t, chi-squared, uniform, binomial, and Poisson distributions.
Section 11.3. Sampling: Perform random permutations and sampling with or without replacement.
Section 11.4. Multivariate Normal: Generate and visualize multivariate data.
Section 11.5. Hypothesis Testing: Conduct t-tests, chi-squared tests, and correlation tests.
Section 11.6. Regression: Fit and interpret simple and multiple linear regression models.

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