STAT 51100 - Statistical Methods

Descriptive statistics; elementary probability; sampling distributions; inference, testing hypotheses, and estimation; normal, binomial, Poisson, and hypergeometric distributions; one-way analysis of variance; contingency tables; regression.

Preparation for Course
P. MA 16600, MA 22800, MA 23000, and MA 16400 ALL with a grade C- or better.

Cr. 3.
Notes
Note: Prerequisites in mathematics and statistics are intended as a guide and may be satisfied through completion of equivalent or more advanced courses. Consent of the course instructor can substitute for completion of specified prerequisites, and students are invited to discuss their eligibility for enrollment with their advisors or the instructor of the course.

Student Learning Outcomes

1. Understand the difference between population parameters and sample statistics.
2. Understand practical data displays: meaning and interpretation of common data displays in the media.
3. Appreciate various interpretations of probability and where they enter into statistical studies.
4. Understand statistical distributions: difference between discrete and continuous random variables. Computing the mean and variance using various important probability distributions such as the Binomial, Hypergeometric, Poisson, Normal, Exponential, Gamma. Computing probabilities using these distributions.
5. Understand statistical distributions of two or more random variables: Sample statistics and their distributions. Understanding the Central Limit Theorem.
6. Understand statistical inference: to understand what this means and what are some practical and important applications. Examples include Confidence Intervals, Tests of Hypotheses for one, two or more populations. Linear Regression with emphasis on the difference between causation and relationships.