Statistics and Applied Data Analysis

A comprehensive understanding of statistics and data analysis is paramount for the fields of data science, data analytics, and machine learning. In the first course of this specialization, you will learn traditional and applied statistics (descriptive statistics, probability, and discrete and continuous probability distributions) from ground zero (i.e., beginner level). The second course is all about inferential statistics and making decisions (sampling distributions, one- and two-sample hypothesis tests, analysis of variance) and creating predictive mathematical models (linear and nonlinear regression). Throughout both of the first two courses, you will learn how to visualize data and solve various statistical problems using Microsoft Excel. In the final course of the specialization, you will use the statistical computing software R (using RStudio) for statistical hypothesis tests, data visualization, and analysis of variance (ANOVA)

• Create mathematical regression models that can be used in a predictive manner
• Perform one-sample and two-sample statistical hypothesis tests
• Perform a variety of statistical tests, create regression models, and analyze data using Microsoft Excel as well as R (RStudio)

• No deep prior experience is required, but basic computer and internet skills are helpful
• Ability to read course instructions in English and complete short practice activities