3.00 Credits
Introduction to the use of probability and statistical inference for business decision making. Various distributions and techniques are presented to prepare the student for parametric estimation and testing. The basic concepts of frequency and probability distributions, measures of central tendency and variance as well as hypothesis testing of means, variances and goodness of fit are presented. There is also brief discussion on non-parametric methods, regression analysis, correlation and price indices. Upon successful completion of this course, students should be able to: Discuss the principles of descriptive and inferential statistics; Compute probabilities using discrete distributions, continuous distributions and counting theory; Investigate concepts in sampling distributions and the Central Limit Theorem; Develop and interpret simple and multiple regression equations and their correlation coefficients; Construct interval estimates for population means; Conduct hypothesis testing for one or two samples; Conduct simple variance testing using ANOVA F distribution principles; Calculate simple index numbers; Execute elementary goodness of fit testing using the chi-squared distribution.
Prerequisite:
MAT 100, MAT 121, MAT 128, MAT 135, MAT 136, MAT 140, MAT 141, MAT 150, MAT 151, MAT 152, MAT 160, MAT 161, MAT 200, MAT 210, MAT 230, MAT 260, or MAT 261