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Math301: Probability and Statistics
Github for Math 301 .
This Github Page contains powerpoints and other useful materials to assist students with Probability and Statistics. See syllabus for assignments and more
Assignments in R
Assignment solutions will be found after students turn them in so that students can see examples of how the questions can be done in R.
Week 1
During this week, we will do a crash course in how to use R and a refresher on Integration. Do not worry if you have not encountered an integral before, we will cover the basics which should be all you need to understand what is happening with probability density functions and other material later on. The slides for the week will be found here
Week 2
During this week, we will explore the beginnings of probability theory and how it can be used. This week will provide the foundations for understanding the rest of the course. The slides for the week will be found here
Week 3 and 4
During these 2 weeks, we will cover a variety of distributions associated with random variables. First, we will cover the probability mass functions, cumulative density functions and expected values of a random variable. Afterwards, we wiil explore the binomial, hypergeometric, geometric, negative binomial,and poisson distributions. The slides for these two weeks will be found here
Week 6 and 7
During this week, we will explore continuous random variables and a host of distributions which have been studied with continuous random variables. The slides can be found here
Weeks 8 and 10
During these weeks we will explore joint distributions for both discrete and continuous rvs. Topics such as corvariance, correlation, and simulations will be covered. Slides are here
Week 11
During this week we will cover point estimators and estimates as well as briefly cover methods of moments.Slides are here
Week 12
Confidence Intervals here
Week 13
This covers hypothesis testing from 1 sample and covers z and t-tests. This will provide most of the material here
Week 14
This is the final week of material for the course. It covers z and t-tests for two samples. The slides can be found here