OS3111 Probability and Statistics for HSI and MOVES

Non-calculus based introduction to basic probability theory and statistics for the non-statistician. Descriptive statistics and graphical techniques. Probability rules including Bayes Rule and independence. Discrete and continuous distributions (Boolean, geometric, binomial, exponential, normal). Expected values, quantiles, variance, covariance, correlation. Expected values and variance of linear combinations of random variables, notably the sample mean. Central Limit Theorem. Student's t-distribution and test, normalization (z-scores), confidence intervals, and introduction to hypothesis testing for the one sample data set, including categorical data. Additional topics may include paired designs, contingency tables and chi-squared test. Prerequisites: None.

Lecture Hours

4

Lab Hours

0

Quarter Offered

  • As Required