Easy Statistics: Linear and Non-Linear Regression

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This course covers the fundamental topics of statistical methodology, enabling you to understand the application and interpretation of linear and non-linear regression modeling.

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71 on-demand videos & exercises
Level: All Levels
5hrs 16mins
Access on mobile, web and TV

What to know about this course

Working with statistics and quantitative reports requires a good understanding of statistics fundamentals and techniques. However, learning and applying new statistical techniques can often be a daunting experience. This is where this course comes into play. To make your experience with statistics a pleasant one, this course gives you comprehensive knowledge of basic principles of the statistical methodology, focusing on linear regression and non-linear regression.

The course starts with an introduction to easy statistics and gives you an overview of the course objectives. Next, you will explore the types of regression analysis that exist and find out how ordinary least squares (OLS) works. To gain a deeper understanding of linear regression and OLS, you will learn to interpret and analyze complicated regression output from OLS. You will also focus on Gauss–Markov assumptions and zero conditional mean. Moving ahead, you will cover non-linear regression, exploring how it works, what the different non-linear regression models are, and the major uses. Towards the end, you will learn to work around with regression modeling with the help of practical examples.

By the end of this video, you will be well-versed with linear and non-linear regression and the basic principles of the statistical methodology. All the resource files are added on GitHub at https://github.com/PacktPublishing/-Easy-Statistics-Linear-and-Non-Linear-Regression

Who's this course for?

If you’re a student, an experienced professional, a manager, or a government worker who wants to learn linear and non-linear regression, regression modeling, and ordinary least squares, then this course is for you. This is a beginner-level course and does not require any prior knowledge of mathematics or statistics.

What you'll learn

  • Understand the basic concept of statistical regression analysis.
  • Become familiar with linear and non-linear regression terminologies.
  • Distinguish between different types of regression methods.
  • Analyze and integrate complicated regression output from ordinary least squares (OLS).
  • Find out the difference between logit and probit transformation.
  • Model non-linear relationships in a linear regression.

Key Features

  • Understand the statistical fundamentals of ordinary least squares (OLS).
  • Gain the confidence to comfortably interpret complicated regression output from OL.
  • Explore regression modeling and its application.

Course Curriculum

About the Author

Franz Buscha

Franz Buscha is a professor of economics at the University of Westminster, which he joined after completing his Ph.D. in economics at Lancaster University. He has been involved in numerous funded research projects from research councils and government departments. He has also contributed to a wide range of projects, including policy evaluation and bespoke econometric advice to UK government departments. Franz has published in leading journals and contributed to numerous policy reports. His research has even been covered by various media outlets. He is an experienced online educator and has published several online courses, including LinkedIn Learning. Franz also has a monthly radio program called Policy Matters on Share Radio.

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