3.00 Credits
This course is designed to give students a tool as well as a language in which they can better understand and analyze the data with which they work and make decisions based on their analyses. It will employ algebra in deriving measures of central tendency and variability for various discrete and continuous distributions and will include the study of the following additional topics: descriptive statistics, inferential statistics, The Central Limit Theorem, the Normal Distribution and its applications, sampling distributions, hypotheses testing, interval and point estimations of population parameters, the Chi-square test with contingency tables, linear correlation and regression, analysis of variance, non-parametric statistics, and applications of statistics in various disciplines. NOTE: Pre-requisite requires a grade of 'C' or higher. Upon completion of this course, students should be able to: Recognize the role of statistics in critical thinking and its applications using descriptive and inferential statistics. Use statistical measures of central tendency and statistical measures of variability to describe, represent and analyze data. Solve problems with bivariate data using scatter diagrams, correlation, and Least-Squares Regression. Solve problems involving the Normal Probability Distribution. Solve problems involving sampling distributions. Solve problems in statistical inference concerned with confidence intervals, minimum sample size determination, goodness of fit tests, and tests for independence and homogeneity. Test hypotheses for one, two, and three or more samples. Compute and interpret nonparametric tests. Use a software package to solve problems in the competencies covered.
Prerequisite:
Prerequisite: MAT 121 or MAT 151 or MAT 152 or MAT 160 or MAT 161 or MAT 200 or MAT 230 or MAT 260 or MAT 261 with a grade of C or better.