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# Regression Analysis / Data Analytics in Regression

## What you’ll learn

• Understand when to use simple, multiple, and hierarchical regression
• Understand the meaning of R-Square and the role it plays in regression
• Assess a regression model for statistical significance, including both the overall model and the individual predictors
• Effectively utilize regression models in your own work and be able to critically evaluate the work of others
• Understand predicted values and their role in the overall quality of a regression model
• Understand hierarchical regression, including its purpose and when it should be used
• Use regression to assess the relative value of competing predictors
• Make business decisions about the best models to maximize profits while minimizing risk
• Critically evaluate regression models used by others
• Learn how to conduct correlation and regression using both IBM SPSS and Microsoft Excel

## Requirements

• Many of the videos use SPSS in running regression models and some use the Microsfot Excel Data Analysis ToolPak. While SPSS is not required to understand the material or follow the videos, if you want to reproduce the analyses on your own, SPSS will be needed. However, other software (such as R, SAS, or Minitab) can be used to reach the same statistical decisions about the regressions models (as are illustrated here).

## Description

November, 2019.

Get marketable and highly sought after skills in this course while substantially increasing your knowledge of data analytics in regression. All course videos created and narrated by an award winning instructor and textbook author of quantitative methods.

This course covers running and evaluating linear regression models (simple regression, multiple regression, and hierarchical regression), including assessing the overall quality of models and interpreting individual predictors for significance. R-Square is explored in depth, including how to interpret R-Square for significance. Together with coverage of simple, multiple and hierarchical regression, we’ll also explore correlation, an important statistical procedure that is closely related to regression.

By the end of this course you will be skilled in running and interpreting your own linear regression analyses, as well as critically evaluating the work of others. Examples of running regression in both SPSS and Excel programs provided. Lectures provided in high quality, HD video with course quizzes available to help cement the concepts. Taught by a PhD award-winning university instructor with over 15 years of teaching experience. At Quantitative Specialists, our highest priority is in creating crystal-clear, accurate, easy-to-follow videos.

Tame the regression beast once and for all – enroll today!

## Who this course is for:

• Anyone interested in learning more about regression analysis.
• This course is not for those looking for a general introduction to statistics course. For this we recommend taking a look at our descriptive statistics or inferential statistics courses. (This course specializes in regression analysis.)
• Those looking to increase their knowledge of regression.