1 / 10

Understanding Correlation and Linear Regression in Predictive Analysis

This text delves into the correlation between X and Y variables, focusing on how z-scores relate to prediction accuracy. It explains the concept of perfect and imperfect correlation, providing formulas and examples to aid understanding. By examining hands-on calculations and discussing variance components, it clarifies the relationship between explained and unexplained variance in regression analysis.

eron
Download Presentation

Understanding Correlation and Linear Regression in Predictive Analysis

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Monday, October 8 Wednesday, October 10 Correlation and Linear Regression

  2. zy = zx When X and Y are perfectly correlated

  3. We can say that zx perfectly predicts zy zy’ = zx Or zy = zx ^

  4. When they are imperfectly correlated, i.e., rxy ≠ 1 or -1 zy’ = rxyzx

  5. Example from hands… • Let’s double-check our understanding of what a correlation coefficient is with respect to z-scores on X and Y variables.

  6. When we want to express the prediction in terms of raw units: zy’ = rxyzx Y’ = bYXX + aYX bYX = rYX (σy / σx) aYX = Y - bYXX _ _

  7. SStotal = SSexplained+SSunexplained N N N Explained and unexplained variance SStotal = SSexplained + SSunexplained

  8. σ2Y’ [ =unexplained] σ2Y [ =total] Explained and unexplained variance r2XY = 1 - σ2Y - σ2Y’ = σ2Y r2 is the proportion explained variance to the total variance.

More Related