MA 487, Introduction to Mathematical Statistics
Course Description and Goals
This is a an introductory, calculus-based course in mathematical statistics. Topics include
- Review of basic probability, including probability spaces, independence, distributions and expected value
- The fundamental theorems of probability:: the law of large numbers and the central limit theorem.
- Estimation, including point estimation and interval estimates for means, variances, and proportions
- Hypothesis testing, including tests for means, variance, and goodness of fit
- Correlation and regression
- Theory of inference, including sufficiency and power.
Course goals include
- A basic understanding of the special notation, language, and point of view of inferential statistics
- A basic understanding of the major areas of inferential statistics, including estimation, hypothesis testing, and regression
- The ability to solve basic computational problems involving estimation, hypothesis testing, and regression
- The ability to model basic statistical problems in science and engineering.
- An improved ability to read, write, speak, and think in mathematical and statistical terms
MA/ST 487 also prepares the student for further study in probability and statistics
Prerequisites
MA 201, Calculus C and either MA 385, Introduction to Probability or ISE 390.
Credit
3 Semester Hours
Grading System
This course is graded A, B, C, D, F. The grade typically depends on a combination of class tests, homework assignments, quizzes, and a comprehensive final exam.
Course Materials
The text is Probability and Statistical Inference, 7'th edition, by Hogg and Tanis, published by Prentice Hall, 2001. An ancillary web site is Virtual Laboratories in Probability and Statistics.