In this course, students work through a thorough refresher of the methods and theories learned in their introduction to statistics course. The course starts from the beginning with basic measures of center and spread which prepares the student for a section on the normal distribution and perhaps the most fundamental theory in statistics: the Central Limit Theorem (CLT). This is followed by discussions on one- and two-sample confidence intervals and hypothesis tests for the difference of means. The course concludes with a section on the use and interpretation of simple linear regression techniques which leaves the student prepared to begin a much more in-depth study of statistical methods provided in the Statistical Foundations for Data Science course. The course is largely example-based and provides opportunities for students to work with the instructor to solve problems with both handwritten and SAS-based solutions.
Statistics, confidence intervals, hypothesis testing, introduction, SAS