11 Useful Tips for Regression Analysis

11 Useful Tips for Regression Analysis

English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 0h 55m | 141 MB


If you need to sort through information to gain insights or make data-driven decisions, regression analysis is a helpful tool in almost any circumstance. On the most basic level, regression analysis reveals relationships between a dependent variable and a collection of independent variables in a fixed dataset. This is crucial for predicting and forecasting, and also helpful for inferring causal relationships between variables. In this course, Franz Buscha moves beyond the basics, showcasing several prominent tips and tricks that will allow you to not only build better regression models, but also present your results in a more impactful way. Through use of practical examples, Franz covers topics like weighted regressions, polynomial variables, and how to deal with missing data in your regression models.

+ Table of Contents

1 Diving deeper into regression models
2 What you should know
3 Weighted regression
4 Factor variables
5 Polynomial variables
6 Fractional variables
7 Model proportions
8 Centering
9 Missing data
10 Standardized estimates
11 Graph estimates
12 Contour plots
13 Animate results