Statistics and Data Analysis with Excel, Part 2

This course is meant to be a direct continuation of "Statistics and Data Analysis with Excel, Part 1." Therefore, it is not recommended to take Part 2 unless you've also taken Part 1. Building on the topics learned in Part 1 of the course (probability, probability mass and density functions, the normal and standard normal distributions), this course dives into a more applied side of statistics. Topics in Part 2 include sampling distributions; one-sample hypothesis tests on the mean, variance, and binomial proportion; two-sample hypothesis tests (comparison of means, variances, and binomial proportions of samples drawn from two populations); simple (straight-line) regression; multilinear regression; and analysis of variance (ANOVA). Statistical techniques are taught with the help of Microsoft Excel, which is an intuitive software package that has many built-in functions and tools for statistical analysis. This course is the second course out of three that comprise the specialization "Statistics and Applied Data Analysis." Course 3 ("Statistics and Data Analysis with R") focuses on statistical analysis in the statistical software package RStudio

• Perform one- and two-sample hypothesis tests on mean and variance
• Create and interpret simple and multiple regression models
• Use ANOVA to compare means across multiple samples

• Basic familiarity with topic concepts and terminology
• Willingness to engage in applied exercises or case studies