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Learn Regression Analysis from Basics for Data Science
Highest Rated
Rating: 4.8 out of 5(12 ratings)
667 students

Learn Regression Analysis from Basics for Data Science

Regression Analysis for Data Science: A Comprehensive Guide from Fundamentals to Applications"
Highest Rated
Created bySandeep Kumar Mathur
Last updated 6/2026
English

What you'll learn

  • Understand how regression analysis fits into the broader context of data science,
  • Develop a deep understanding of the concepts of regression analysis, including its applications.
  • Learn how to interpret regression coefficients and understand practical approach
  • Learn how to deal with common issues in regression analysis

Course content

2 sections • 20 lectures • 1h 42m total length

  • Regression Analysis : An Introduction6:35

    Explore the basics of regression analysis, including dependent and independent variables, simple and multiple regression, and predicting a variable from others with linear regression models.

  • Importance or uses of Regression Analysis2:34
  • Linear Regression and Regression Lines5:11
  • Illustration14:41
  • Illustration25:09
  • Illustration36:33
  • Illustration44:27
  • Regression Coefficients and their Properties13:55
  • Illustration11:11

    Learn how to compute the correlation coefficient from two regression coefficients using the direct formula r = sqrt(0.5 × 1.3), yielding r ≈ 0.806.

  • Illustration23:11
  • Illustration31:58
  • Illustration42:29
  • Illustration53:39
  • Illustration61:38
  • Illustration71:59
  • Calculating Mean Value and Regression coefficients5:03
  • Illustration112:28
  • Illustration26:27

    Identify the regression line by comparing two equations for y on x and x on y, then compute slopes b_x_y and b_y_x and the correlation r.

  • Illustration35:51

    Learn regression analysis by deriving the regression equations for x on y and y on x, and compute coefficients b_xy, b_yx, correlation r, and means x-bar and y-bar.

  • Formulae for finding out Regression Coefficients7:45

    Learn to calculate regression coefficients using direct and shortcut methods for x on y and y on x, with formulas for r and the slopes b_xy and b_yx.

Requirements

  • Elementary knowledge of Math and Statistics

Description

Regression analysis plays a critical role in data science and machine learning. It is a fundamental statistical technique used to understand the relationship between a dependent variable and one or more independent variables.

One of the primary applications of regression analysis in data science and machine learning is prediction. Regression models can be used to predict the value of a dependent variable based on the values of independent variables.

The course covers the following areas :

Regression Analysis An Introduction

Importance or uses of Regression Analysis

Linear Regression and Regression Lines

and illustrations

Upon completion of the course, students will have a solid understanding of regression analysis and its applications. They will be able to use regression models to analyze data, make predictions, and draw meaningful conclusions. This course is ideal for students pursuing a career in data analysis, statistics, or any field that involves analyzing complex data sets.

You'll receive support through a Q&A section, and the course is continually updated based on student feedback, with plans to add new topics in the future.

So why wait? Enroll today and take the first step toward achieving your goals. With the right tools and support, you can make your dreams a reality and achieve the high score you deserve. Don't miss out on this opportunity to excel and boost your confidence.



Who this course is for:

  • Data Science, Machine Learning deep learning students and professional

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