Final answer:
The statement that one test for model adequacy is to check the normality assumption by plotting residuals on Normal graph paper is true. Normal probability plots are used for this purpose, and several assumptions about residuals are considered, including normal distribution, homoscedasticity, and independence.
Step-by-step explanation:
One of the tests for model adequacy is to check the normality assumption usually by plotting residuals on Normal graph paper. This statement is true. Checking for normality of residuals is a common method used to assess whether the data meets the assumptions necessary for certain statistical analyses, including linear regression.
In linear regression analysis, several assumptions are made about the residuals, which are the differences between the observed and predicted values of the dependent variable:
- The residuals are normally distributed.
- The residuals have the same variance for all predicted values (homoscedasticity).
- The residuals are independent of each other with no recognizable patterns.
Graphical methods, such as a normal probability plot (or Q-Q plot), help in visualizing if the residuals roughly follow a straight line, which would suggest that they are normally distributed. If the plot deviates significantly from a straight line, it could indicate violations of the normality assumption.
Other considerations include the size and randomness of the sample, which affect the validity of the normality test - larger samples provide a better approximation to the normal distribution.