The purpose of blocking in experimental design is: a. to give the quarterback enough time to throw the ball. b. to control for multiple variables in an experiment. c. to prevent response bias from entering into the experiment. d. to keep the subjects from knowing if they are in the treatment group. e. to keep the experimenter from knowing which subjects are in the treatment group.

In statistics, blocking refers to the arrange of experimental units in groups, where each subject have a specific characteristic in common, for example the gender.

So, by dividing the sample into blocks, where each block is almost independent one to another, it helps to manage studies with multiple variables, which it can imply a higher difficulty when the research have to analyse results, because they need to demonstrate or reject a specific relation between variables, if there are too many, it's better to divide the sample in to specific groups, classified depending on their particular characteristics which make them independent, that is, one group doesn't affects other groups.

Using this method in the experimental design, researches are assuring the reliability of the results. Therefore, the correct option is B: blocking has the purpose of controlling multiple variables in an experiment.

  b.   the average rate of change of f(x) is less than the average rate of change of g(x).

step-by-step explanation:

since the length of the interval is the same in each case, we only need to compare the change in y-value to see which is greater.

so the change in y-value for function f is (6 )) = 9.

the table tells us

so the change in y-value for function g is (31 -1) = 30.

the change in y-value of f(x) on the interval is less than the change in y-value of g(x) on the same interval, so the average rate of change of f(x) is less than the average rate of change of g(x).

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step-by-step explanation: