Please explain answers. Thank you! 11. The interpolation forecast represents a f
ID: 3041739 • Letter: P
Question
Please explain answers. Thank you!
11. The interpolation forecast represents a forecast using the actual data from which the regression equation was computed
True or False.
12. As long as the residuals create a random pattern around the zero line in a residual plot, the linear regression equation can be considered an appropriate fit to the data.
True or False
13. When a linear equation is an appropriate model for a dataset, the distribution of data around the regression line should suggest a series of _________ distributions centered on the regression line with constant variance across the range of the chart.
a.) rectangular
b.) skewed
c.) normal
d.) binomial
14. When the variability around the regression line is the same for all values of the independent variable X this is referred to as__________
a.) homoscedasticity
b.) interpolation variability
c.) heteroscedasticity
d.) quadratic variation
15. When an independent variable in a multiple regression model includes a value of X to a higher power, such as X squared, and this model produces a higher value of R-squared than a linear model, this suggests that the residual plot for the linear equation did not produce a random pattern around the zero line of the residual plot.
True or False
Explanation / Answer
11. True , interpolation uses regression for predicting the values of Y at given values of X.
12. True . Because postive value of residual shows prediction was too low and negative values shows prediction was too high , 0 shows exactly correct prediction.
13. Normal
14.homoscedasticity
15. False , higher r squared value means the model is fir for the data