APMA 3120 Chapter 13: Chapter 13- Regression

• School: University of Virginia
• Department: Applied Mathematics
• Course: APMA 3120
• Professor: James Lark

Document Summary

Strength of the relationship between each predictor and dv while controlling the other predictor variables in the model. Pearson correlation coefficient is a simple linear regression coefficient that"s been standardized. 1: simple linear regression begins with assumption that the two variables are linearly related. Every increase of a given size in value on the x variable, the predictor/iv, there is a corresponding increase/decrease (depends on positive/negative correlation) of a given size in the y variable, the dv/outcome. ^y =bx +a ^y =predicted value of y var ;b=unstandardized regressioncoefficient , slope=r x sy. B is the regression coefficient (slope of the regression line) and x is value of variable . If the relation was weaker, the data points would be scattered and the lower left to upper right trend would be less clear xi. Regression equation allows us to find predicted values for y given any value of x and produce the regression line xii.