GEP/GFR: Meets Mathematics. Organization and presentation of data, summary of descriptive measures, probability, binomial and normal distributions, sampling natural populations and the estimation of population parameters, hypothesis testing, chi-square analysis experimental designs and the analysis of variance, linear regression and correlation, and non-parametric statistics. Students will be introduced to statistical computing. All the statistical procedures will be illustrated using data from biology and the health sciences. Prerequisites: MATH 150 or placement into 151. Notes: Not open to students who have passed or are concurrently taking STAT351, 355, 356, 453, or CMPE 320. This course does not satisfy the statistics requirement for CMSC majors and does not qualify as part of the MATH major or minor.

Uses data from a variety of disciplines to explore topics in statistical data analysis, estimation, and inference. The following topics will be covered: graphical displays; measures of position, central tendency, and variability; basic probability rules; discrete probability distributions; binomial distribution; normal and standard normal probability distributions; sampling distributions; the t distribution; confidence intervals and hypothesis tests for one mean or proportion; confidence intervals and hypothesis tests for two means or proportions; correlation and simple linear regression.