PSY201H1 Chapter Notes - Chapter 7: Homoscedasticity
Document Summary
Regression considers using the relationship between two or more variables for prediction. Regression line is a best fitting line used for prediction. The least-squares regression line is the prediction line that minimizes the total error of prediction according to least-squares. The standard error of estimate is a measure of the average deviation of the prediction errors about the regression line. Minimize prediction errors in the x variable. Maximize ability to predict x given y. Minimize prediction errors in the y variable. Maximize ability to predict y given x. To measure the magnitude of prediction errors. The amount of error involved in predicting a score from the regression line. The average amount of unexplainable variation in y given x. We must assume that the variability of y remains constant as we go from one x score to the next. The larger the value, the less accurate the prediction. The smaller the value, the more accurate the prediction.
