1 / 8

Correlation and Regression Analysis

Correlation and Regression Analysis. By R. D. Wooten Statistical Consulting and Analytics Group (SCAG) University of South Florida. Correlation Analysis. Scatter plot of Turbidity (Y) over Forest (X). PCA Loading weights. Variances of principle components. Multiple Linear Regression.

fala
Télécharger la présentation

Correlation and Regression 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. Correlation and Regression Analysis By R. D. Wooten Statistical Consulting and Analytics Group (SCAG) University of South Florida

  2. Correlation Analysis

  3. Scatter plot of Turbidity (Y) over Forest (X)

  4. PCA Loading weights

  5. Variances of principle components

  6. Multiple Linear Regression Fitting six variables with eight data points is not recommended as it artificially inflates the coefficient of determination. The full model Y~X1+X2+ X3 + X4 + X5+X6 shows an ; however, nothing is significantly contributing as some of the variables are confounded. Moreover, I can make by including the interaction between X3 and X6; however, this is an exact solution with no measure of error - eight equations and eight unknowns. Consider the model Y~ X1 + X4 + X5 that is, Y ̂=11.2+0.35X1-0.24X4-4.42X5;R2=0.7311 This model explains 73.11% of the variance in Turbidity; that is, approximately 73% of the average turbidity is explained by the Developed, Wetland and Bare land with all variables found to be significant at the 5% level.

  7. PCA revisited

  8. Thank you Any questions?

More Related