Regression Analysis / Data Analytics in Regression
What you will 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
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Comidoc Review
Our Verdict
This Udemy course on Regression Analysis and Data Analytics ticks several boxes for beginners looking to understand the basics of this widely used statistical technique. It does an excellent job of breaking down complex concepts into simpler terms, using real-world examples to enhance comprehension. However, the course falls short in providing a detailed background on certain topics like ANOVA and correlation, while failing to address advanced linear regression techniques entirely. Additionally, some resources provided are not compatible with various systems, leading to potential accessibility issues for learners. Consider this course if you're seeking an introduction or refresher but explore other options if advanced material is your priority.
What We Liked
- Covers both theoretical and practical aspects of regression analysis
- Ideal for beginners wanting an introduction to regression, as well as those needing a refresher
- Instructor explains concepts clearly and at a manageable pace
- Real-world examples and APA write-up examples provided
Potential Drawbacks
- Lacks in-depth explanation of some concepts like ANOVA, correlation, and outliers
- Resources have compatibility issues; file types not always openable and SPSS access required
- More advanced aspects of linear regression are not covered within the scope of this intro course
- Lacks a comparison between Pearson and Spearman correlations, as well as two-tailed vs one-tailed interpretations