Udemy – Applied Linear Regression Analysis (using R,SPSS,SAS,Python) 2022-5

Udemy – Applied Linear Regression Analysis (using R,SPSS,SAS,Python) 2022-5 Downloadly IRSpace

Apr 17, 2025 - 11:22 Updated: Apr 20, 2025 - 21:23

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Udemy – Applied Linear Regression Analysis (using R,SPSS,SAS,Python) 2022-5

Applied Linear Regression Analysis (using R,SPSS,SAS,Python) This course teaches you how to do linear regression analysis from the very basic level, to advanced/expert level, depending on your needs. A fundamental teaching (or knowledge transfer) philosophy which I have adopted for this course is that students should learn and understand the ‘fundamentals of the analytics methodology’ first, before learning how to apply those methodologies to do data analysis via software. This is different from some (similar) courses where the focus tends to be on teaching you how to use a software for running regression analysis (without deep understanding of regression methodology itself). My intention is for you to develop mastery of regression analysis as a modelling technique first, and have the confidence to tackle any modelling/prediction problem which requires linear regression modelling. This means that the first part of the course is largely software-independent, although I use R-software to demonstrate the concepts and also to help with your understanding and interpretation of software outputs for regression analysis.

I believe that once you learn this important methodological part well, you should be able to use any software for applied regression analysis. As you will find out, the codes and steps/processes for linear regression analysis are very similar across the various software (including the four which we use in this course). Critically important also, is that outputs from regression analysis are incredibly and understandably similar in structure, across most software. Hence, my view (and reason for adopting this approach) is that, if you understand the fundamentals of regression methodology well initially, you should then be able to subsequently use any software and interpret any regression analysis outputs, and also should easily be able to move across and use a variety of software (provided you learn how to use or code in that particular software, of course).

What you’ll learn

Understanding how linear regression analysis works, including theoretical foundations, techniques, worked examples, live demonstrations of four software
Fundamentals and requirements for doing good linear regression, including data requirements, and tools for preliminary investigations (eg graphical plots)
How to use a variety of tools, measures, and metrics for evaluating if your linear regression model is a good fit for your data, and ways to improve the fit
Doing linear regression analysis in any of (or all) the four software covered, namely R, SPSS, SAS, Python. You will see learn from demonstrations of software
This course covers applied linear regression analysis fully. So you should not need to do a similar course again(except to learn to use a different software)

Who this course is for

Statistical modellers, data analysts, data scientists, students, and researchers who want to properly understand how linear regression works in practice/applications, AND/OR people who are interested in learning how to do regression analysis using one or more of the software used in this course (i.e SAS, R, SPSS, Python).
People who are interested in understanding how the four different software (used in this course) are used for linear regression analysis

Specificatoin of Applied Linear Regression Analysis (using R,SPSS,SAS,Python)

Publisher : Udemy
Teacher : Charles R Lawoko
Language : English
Level : All Levels
Number of Course : 115
Duration : 13 hours and 52 minutes

Content of Applied Linear Regression Analysis (using R,SPSS,SAS,Python)

Applied Linear Regression Analysis (using R,SPSS,SAS,Python)

Requirements

Some familiarity with basic statistical terminologies (typically first or second year university introductory course in applied statistics or statistical data analysis). Some basic understanding of mathematical equations if you want to understand the fundamental theory part (although this is not a pre-requisite for the course.
I am assuming that you are able to use whichever software you choose to learn in ( i.e of the four software used). For whatever software you choose to use, you should be able to run that software, bring in data, etc, as a minimum.