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Which term describes the difference between the actual and predicted values of a dependent variable?
The residual is the difference between the actual value of a dependent variable and the value predicted by the estimated regression line.
What is standardized predicted value?
Unstandardized . The value the model predicts for the dependent variable. Standardized . A transformation of each predicted value into its standardized form. That is, the mean predicted value is subtracted from the predicted value, and the difference is divided by the standard deviation of the predicted values.
When is the difference between the actual value and predicted value?
Each actual value has a predicted value and hence each data point has one residual. If the difference between the actual value and the predicted value is positive, then the data points are above the regression line. If the difference between the actual value and the predicted value is negative, then the data points are below the regression line.
How to predict the value of a dependent variable?
The coefficients in the equation define the relationship between each independent variable and the dependent variable. However, you can also enter values for the independent variables into the equation to predict the mean value of the dependent variable.
How are data points related to the predicted value?
Each actual value has a predicted value and hence each data point has one residual. If the difference between the actual value and the predicted value is positive, then the data points are above the regression line.
How can you make predictions with regression analysis?
Regression predictions are for the mean of the dependent variable. If you think of any mean, you know that there is variation around that mean. The same applies to the predicted mean of the dependent variable. In the fitted line plot, the regression line is nicely in the center of the data points.