### R for Data Science: Regression Methods

**Overview/Description**

**Expected Duration**

**Lesson Objectives**

**Course Number**

**Expertise Level**

**Overview/Description**

The programming language has become an essential skill for statistical computing and graphics, the tool of choice for data science professionals in every industry and field. R creates reproducible high-quality analyses, and allows users to take advantage of its great graphic and charting capabilities. In this 8-video Skillsoft Aspire course, you will discover how to apply regression methods to data science problems by using R. Key concepts covered in this course include preparing a data set before creating a linear regression model how to create a linear regression model with the lm method in R; and extracting statistical results of a linear regression problem. You will also learn how to test the predict method on perform the preparatory steps needed to create a logistic model; and how to apply the generalized linear model (glm) method on a logistic regression problem. Finally, learners see how to create a linear regression model and use the predict method on a linear model.

**Expected Duration (hours)**

0.6

**Lesson Objectives**

**R for Data Science: Regression Methods**

**Course Number:**

it_dsrfdsdj_04_enus

**Expertise Level**

Intermediate