QUESTION 30 What does the R-squared value tell you in linear regression? (CHOOSE ALL THAT APPLY) The strength of the relationship between the explanatory variable and the response variable. O If there is a positive relationship between the explanatory variable and the response variable. How much of the variance in the response variable can be accounted for by the explanatory varia If there is a negative relationship between the explanatory variable and the response variable.

Using a sample of 46 college students, we want to determine if there is a significant correlation between weight (in lbs.) and weekly exercise (in minutes). The results of a correlation and regression analysis are indicated in the Excel output below. The mean weight (the independent variable) was 166.80 lbs., and the mean weekly exercise time (the dependent variable) was 158.83 minutes.         SUMMARY OUTPUT                           Regression Statistics           Multiple R 0.027082077           R Square 0.000733439           Adjusted R Square -0.021977165           Standard Error 79.41761298           Observations 46                         ANOVA               df SS MS F Significance F   Regression 1 203.6896 203.6896 0.032295 0.858207   Residual 44 277514.9 6307.157       Total 45 277718.6                         Coefficients Standard Error t Stat P-value Lower 95%…

19. You might think that increasing the resources available would elevate the number of plant spe- cies that an area could support, but the evidence suggests otherwise. The data in the accompany- ing table are from the Park Grass Experiment at Rothamsted Experimental Station in the U.K., where grassland field plots have been fertilized annually for the past 150 years (collated by Harpole and Tilman 2007). The number of plant species recorded in 10 plots is given in response to the number of different nutrient types added Plot 1 2 3 4 5 6 7 8 9 10 Number of nutrients added 0 0 0 3144 E2 3 Number of plant species 36 36 32 34 33 30 20 23 21 16

Which statement is not correct for multiple regression model? When we interpret this categorical variable, we would say the change we observe when one switches from the reference category to the specific category. The reference category will not be displayed in our model results. If we include a categorical variable with more than two values (e.g., religion) as an independent variable, we want to include a dummy variable for all categories except for two. We can include more than two categorical variables in the model. The value of the independent variable not included in the model is called "reference category."