Probability and Statistical Inference

Introduction

This course is an introduction to probability and statistical inference with R. Rstudio is an interface for R, to download go to the Rstudio website.

1. Introduction to Probability:
   • Measures of Location;
   • Mathematical Probability;
   • Counting;
   • Conditional Probability and Bayes Law.
2. Introduction to Distributions:
   1. Discrete:
      • Bernoulli;
      • Binomial;
      • Poisson.
   2. Continuous:
      • Normal Distribution.
3. Introduction to Inference.
4. Introduction to Hypothesis testing:
   • Z-test;
   • Chi-squared test;
   • t-test.
5. Regression:
   • Simple linear regression;
   • Categorical regression;
   • Logisitic regression.

GitHub Course Code Repository

This repositry has the R code for the examples in the course

References

Essential Reading: (author, title, publisher)

Devore & Peck - Statistics: The exploration and analysis of data (2011)

Supplemental Reading: (author - title, publisher, date)

Gareth, J, et al. - An introduction to statistical learning. Vol. 112. New York: springer, 2013.

Dalgaard, P. - Introductory Statistics with R, Springer 2008

James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning (Vol. 112, p. 18). New York: springer. book website

Popular Science: (author, title, publisher, date)

Fry, H. - Hello World: How to be Human in the Age of the Machine, Doubleday, 2018

Rosling, H, Rosling, O, Rosling Ronnlund, - Factfulness: Ten Reasons We're Wrong About The World - And Why Things Are Better Than You Think, Sceptre, 2019

Silver, N, - The Signal and the Noise: The Art and Science of Prediction, Penguin, 2013

Podcasts: (name, website)

Deep Mind: Podcast, https://deepmind.com/blog/article/welcome-to-the-deepmind-podcast

Freakonomics Podcast, http://freakonomics.com/

More or Less: Behind the Stats https://www.bbc.co.uk/programmes/p02nrss1/episodes/downloads