Math 130 or higher.
4.00
Topics include: data presentation, measures of central locations and dispersion, probability and probability distributions, estimation, hypothesis testing, simple and multiple regression models. The use of Excel and SPSS will be emphasized throughout the course. Prerequisite: Math 130 or higher. 1 term - 4 credits (4 hours per week). Normally offered each semester.
Quantitative Reasoning
MATH 130, MATH 134, MATH 146 OR MATH 165
4.00
Application of statistical analysis to real-world business and economic problems. Topics include data presentation, descriptive statistics including measures of location and dispersion, introduction to probability, discrete and continuous random variables, probability distributions including binomial and normal distributions, sampling and sampling distributions, statistical inference including estimation and hypothesis testing, simple and multiple regression analysis. The use of computers is emphasized throughout the course. Normally offered each semester.
Quantitative Reasoning
MATH 130, 134, 146, or 165; Honors Course; GPA of 3.2
4.00
Application of statistical analysis to real-world business and economic problems. Topics include data presentation, descriptive statistics including measures of location and dispersion, introduction to probability, discrete and continuous random variables, probability distributions including binomial and normal distributions, sampling and sampling distributions, statistical inference including estimation and hypothesis testing, simple and multiple regression analyses. The use of computers is emphasized throughout the course. Prerequisite: MATH 130, MATH 134, MATH 146, or MATH 165 Honors Course GPA of 3.2 or higher required. 1 term - 4 credits Normally offered every year.
Quantitative Reasoning
STATS 250
4.00
This application-oriented course is designed to go beyond the topics covered in STATS 250. It includes topics like Analysis of Variance (ANOVA), special topics in regression analysis and index numbers. Further, time series data, which consist of values corresponding to different time intervals, are analyzed. The objective is to examine past time series values to forecast, or predict future values. Seasonal variations are also incorporated in the forecasts. The course will provide useful computer skills involving various statistical packages and is an excellent preparation for graduate work in business and social sciences.
Social Science
0.00
This course is taken as a co-requisite to Stats240. The recitation is a hybrid course. Once every two weeks students meet with an instructor to do work that enhances understanding of the course material. On alternate weeks students work on individual and group homework.
