This class will be used to tackle all the problems in probability and statistics for all students taking mathematics courses. Analysis and statistical programming courses such as R, STATA, SPSS, MINITAB and SAS will also be handled in this class

This class will help you learn how to use statistical analysis to assess two mutually exclusive theories about the properties of a population using available sample data. These theories are often referred to as null and alternative hypotheses. The student will also learn when to reject or fail to reject the null hypothesis, learn the effect, p-value calculation both manually and by use of software, significance level and the associated types of errors. Z-tests, t-tests, chi-square test, anova test, binomial test, one sample and two sample tests will be handled in this class.

This class will make you have essential skills in statistical programming using R that will be effective in data analysis. You will learn more about installation of R software and its configuration that will create statistical programming environment. This class entails a variety of issues that pertains statistical programming and computing which includes programming in R, reading data into R, how to access R packages, how to write R codes, debugging as well as creating well commented R codes.