A researcher is studying the relationship between hours studied per week and GPA. The researcher developed the following regression equation:: Y = 2.55 + 10(X). If a student studies 10 hours per week, the researcher would predict the student's GPA to be:

The police chief believes that maintenance costs on high-mileage police vehicles are much higher than those costs for low-mileage vehicles.  If high-mileage vehicles are costing too much, it may be more economical to purchase more vehicles.  An analyst in the department regresses yearly maintenance costs (Y) for a sample of 200 police vehicles on each vehicle’s total mileage for the year (X). The regression equation finds: Y = $50 + .030X with a r2 of .90 What is the IV? What is the DV? If the mileage increases by one mile, what is the predicted increase in maintenance costs?  If a vehicle’s mileage for the year is 50,000, what is its predicted maintenance costs? What does an r2 of .90 tell us? Is this a strong or weak correlation? How can you tell?

A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-1.145 b=20.742 r?=0.508369 r=-0.713 Use this to predict the number of situps a person who watches 2.5 hours of TV can do (to one decimal place)

A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (xx) and number of sit ups a person can do (yy). The results of the regression were: y=ax+b a=-1.152 b=30.418 r2=0.703921 r=-0.839      1. Use this to predict the number of sit ups a person who watches 2.5 hours of TV can do, and please round your answer to a whole number