Simple Linear Regression Basics using R
3.8 (7 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
18 students enrolled

Simple Linear Regression Basics using R

A guide to understanding basic Simple Linear Regression using R
3.8 (7 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
18 students enrolled
Created by Oscar Adimi
Last updated 5/2016
English
English [Auto-generated]
Current price: $13.99 Original price: $19.99 Discount: 30% off
5 hours left at this price!
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This course includes
  • 42 mins on-demand video
  • 3 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • Get familiar with the basic concepts of linear regression through visual analysis and statistical tests
  • Get a deeper understanding of the Simple Linear Regression equation and its components as well as evaluating the goodness of fit of model through model diagnostic
Course content
Expand all 6 lectures 41:53
+ Data Analysis
4 lectures 32:35
Data Investigation and Visualization Part 1
08:12
Data Investigation and Visualization Part 2
08:54

This is the first part of the modeling process where the first model iteration consists of modeling with outliers

Preview 08:01
Data Modeling Part 2
07:28
Requirements
  • Download and install R /R studio
Description

This is an introductory course to Simple Linear Regression, one of the most basic courses in Statistics.

This course is most suitable for students of professionals with basic knowledge or beginning level in Statistics and R coding. It also fits for anybody who want to explore the field of statistics using R in any discipline.

We will start with an introduction section where I will explain the regression equation with a detailed example. Next, we will cover the essentials of modeling. At this section, I added an emphasis to data cleaning which is essential nowadays with big data issues. Then will follow visualization, modeling and diagnostics.

We will be using R studio which is a nice coding open source environment. R studio is suitable for academic and professional needs.

This course is important in the sense that data analysis needs are constantly growing with the emerging complexity of data. Quick data driven decisions need to be made at the management level. Data Analytics is the most efficient way to get the most accurate information to make decisions.

Who this course is for:
  • Students of Professionals with beginner or intermediate level in statistics and R coding