Question 1 Which of the following is a source of variation in the response variable used in a regression analysis? 0 Unexplained noise 0 pvalue 0 None of the answers are correct 0 Extrapolation A homeowner in Minnesota recorded the outdoor average daily temperature (degrees F) and how much natural gas she used to heat her home over a 23-month period. A scatterplot indicates that temperature and gas usage appear to have a linear relationship. The data were used to estimate the following regression equation: y = 1125 -16x where natural gas use is the response and temperature is the explanatory variable. How much would her natural gas use change for a 1 degree F increase in outdoor temperature? 0 Natural gas use will decrease by 1125 units 0 Natural gas use will decrease by 16 units 0 Natural gas use will increase by 16 units 0 Natural gas use will increase by 1125 units Question 3 1 pts For the regression line in the previous problem, how much natural gas would you predict the homeowner would use on a day when the average outdoor temperature is 35 degrees F? O 565 units 0 1685 units 0 16 units 0 1125 units Question 4 1 pts The regression line t by the Minnesota homeowner had a R2 of 0.98. A homeowner in New Mexico t a similar regression using his own local temperature and gas usage and obtained a R2 of 0.56. Scatterplots show that the data are linear for both homeowners. Which homeowner will be better able to predict natural gas usage? 0 The homeowner in New Mexico because the homeowner in Minnesota is extrapolating 0 Both homeowners will make equally accurate predictions 0 The homeowner in New Mexico because his model as a lower R2 O The homeowner in Minnesota because her model has a higher R2 Question 5 1 pts The Minnesota homeowner collected her data when the outdoor temperature ranged from 25 degrees F to 40 degrees F. The weather forecast for next week predicts that outdoor temperatures will average 10 degrees F. The homeowner would like to use her regression equation to predict her natural gas usage for next week. What would be your recommendation? 0 No, she should not predict her gas usage because that would be extrapolating 0 Yes, she should predict her gas usage because the data have a linear relationship 0 No, she should not predict her gas usage because the sample size is too low 0 Yes. she should predict her gas usage because the R2 is high Question 6 1 pts The difference between an observation and the tted regression line is called what? 0 Slope O Intercept 0 Residual O Explained variation Question 7 1 pts A regression model is to be t using year in high school -- freshman, sophomore, junior, senior -- as an explanatory variable. How many variables will need to be included in the regression model to represent year in high school? 05 04 O1 03 Question 9 1 pts A regression line in which there is no relationship between the response and the explanatory variables would have what slope? O Innity 00 0 None of the answers are correct 01 Question 10 1 pts Why is it important to plot your data before running a regression? 0 All of the answers are correct 0 To make sure there is a linear relationship between the response and explanatory variable 0 To look for statistical signicance 0 To determine if some explanatory variables should be excluded from the analysis Question 8 Refer to the regression output below. Estimate Std. Error t value Pr (> | t 1) (Intercept) 10.56 3.0222 3.4941 0.0015 x1 7.65 6.4834 1.1799 0.2473 x2 2.17 0.8103 2.6779 0.0119 Which variable is most likely to be related to the response? O Only x2 because it is statistically significant while x1 is not O The intercept because it has the largest estimate and smallest p-value O Both the intercept and x2 because they are both statistically significant O Only x1 because it has a larger estimate than x2