Description
Applied Linear Regression Analysis (using R, SPSS, SAS, Python), the training course on Applied Linear Regression Analysis (using R, SPSS, SAS, Python) has been published by Udemy Academy. This course will teach you how to perform linear regression analysis, depending on your needs, from the basic level to the advanced and specialized level. The basic teaching philosophy (knowledge transfer) that I have chosen for this course is that students should first learn the basics of analytical methodology and understand how to apply these methodologies to perform data analysis through software. to take This differs from some training courses where the focus is on teaching how to use a software to perform regression analysis (without a deep understanding of the regression methodology itself). My intention is that you will initially develop mastery of regression analysis as a modeling technique, and have the confidence to tackle any modeling or forecasting problem that requires linear regression modeling.
This means that the first part of the course is very software dependent, although I use R-software to demonstrate the concepts as well as to understand and interpret the software outputs for regression analysis. I believe that once you have mastered this important part of the methodology, you should be able to use any software for applied regression analysis. As you will notice, the codes and steps for linear regression analysis are very similar among different software (including the four we use in this lesson).
What you will learn
- Understanding how linear regression analysis works, including theoretical foundations, techniques, worked examples, showing four software
- Principles and requirements of performing good linear regression, including data requirements, and tools for preliminary research (eg graphical plots)
- How to use a variety of tools and metrics to evaluate whether your linear regression model is a good fit for your data, and ways to improve it
- Performing linear regression analysis in each of the four softwares covered, namely R, SPSS, SAS, Python.
- This course thoroughly covers applied linear regression analysis. So you don’t have to take the same course again
Who is this course suitable for?
- Statistical modelers, data analysts, data scientists, students, and researchers who want to properly understand how linear regression works in practice, or people interested in learning how to perform regression analysis using one or more The software used in this course.
- People who are interested in understanding how to use four different software (used in this course) for linear regression analysis.
Characteristics of Applied Linear Regression Analysis course (using R, SPSS, SAS, Python)
- Publisher: Udemy
- teacher : Charles R Lawoko
- English language
- Education level: all levels
- Number of courses: 115
- Training duration: 13 hours and 52 minutes
Chapters of Applied Linear Regression Analysis (using R, SPSS, SAS, Python)
Course prerequisites
- 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 (ie 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.
Pictures
Sample video
Installation guide
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download link
File(s) password: www.downloadly.ir
Size
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