Il When making inferences about population standard deviation, what distribution should we use? Select one: Q a. tdistribution O b. F-distribution O c. Normal distribution 0 d. Chi-squared distribution When testing for Individual Significance in a regression model, what is the purpose? Select one: Q a. Find R-Squared for the estimated regression equation 0 b. Detect leverage in the model 0 c. Assess if there is a significant relationship between the dependent variable and a particular independent variable 0 d. Calculate the Goodness of Fit for the regression model In a regression model, will a test for Overall Significance yield the same result as a test for Individual Significance? Select one: Q a. It depends on the data set 0 b. It depends on the nature of the dependent variable 0 c. Yes, but only if there is one independent variable 0 d. No, the outcomes will be different for the two tests Il What is the implication of a regression coefficient which is significantly different from zero? Select one: Q a. The corresponding variable is unrelated to the dependent variable at the population level 0 b. The coefficient is zero at the population level 0 c. The corresponding variable is related to the dependent variable at the population level 0 d. The variable is insignificant In a Multiple Linear Regression model, if you are interested in looking into the relationship between the dependent variable and a specific independent variable, what test statistic would you use? Select one: Q a. F O b. DurbinWatson O c. t Q d. Cook's D You have estimated two different models. When comparing the Adjusted PSquared for the two models, one has a higher value. What's the implication? Select one: Q a. The model with higher Adjusted lieSquared is simpler O b. The model with higher Adjusted RSduared has a higher Goodness of Fit value 0 c. The model with higher Adjusted RSduared is better in terms of prediction 0 d. The model with higher Adjusted RSduared is better when considering both prediction and simplicity When you find and interpret a pvalue, what's the underlying assumption? Select one: Q a. The null hypothesis is true O b. It is greater than the test statistic O c. Neither of the hypotheses is true 0 CI. The alternative hypothesis is true What's the implication of a low R-Squared in a regression? Select one: Q a. The Regression Sum of Squares is high O b. The model overrides the leastsquares estimation 0 c. The Error Sum of Squares is low Q d. The model explains a low share of the variability in the dependent variable A regression model was estimated to look into the relationship between the number of hours spent on volunteering activities and the number of years of education. The outcome was a p-value of 0.063 for the F-statistic. With a 5% level of significance, it can be said that: Select one: Q a. We rejected the null hypothesis O b. Volunteering hours is unrelated to years of education 0 c. There is a significant relationship between volunteering hours and years of education 0 d. The regression model is significant A data set contains a variable 'Country of Origin' that states the country in which the product was manufactured. This is an example of a: Select one: Q a. Dummy variable 0 b. Quantitative variable 0 c. Categorial variable 0 d. Dependent variable A regression of Sales [$1,000] on Advertising [$1,000] and Market Share [%] resulted in the following output. Refer to the results and interpret the estimated slope for Market Share. Coefficients Intercept 810.00 1.31 Advertising 0.25 3.13 Market Share 187.00 2.18 Select one: Q a. If Market Share increases by 1% while holding Advertising constant, Sales are expected to increase by $997,000 0 b. If Market Share decreases by 1% while holding Advertising constant, Sales are expected to increase by $187,000 0 c. If Market Share increases by 1%, while holding Advertising constant, Sales are expected to increase by $187,000 0 d. If Market Share increases by 187% while holding Advertising constant, Sales are expected to increase by $1,000 The regression output below shows the estimated relationship between Price and the independent variables Curb Weight, Horsepower, and Acceleration. If performing a test for overall significance for this model, what would your null hypothesis be? E 10 Finis Coefficients P-value Lower 95% Intercept 179.97 112.86 1.60 0.14 425.87 Curb Weight -0.01 0.02 -0.85 0.41 -0.05 Horsepower -0.15 0.15 -1.03 0.33 -0.48 Acceleration 3.14 1.30 2.42 0.03 0.31 Select one: Q a. p s a O b- 151 = 132 = 133 = O O C. [51 = 0 Q 01. At least one of the parameters not equal to zero Please refer to the regression output below. At a 5% level of significance, [ how many significant variables do we have? [ mm \"am-mu -m- -m \"m Select one: Upper 95% 296.13 O a. There is one significant variable 0 b. There are three significant variables 0 c. There are five significant variables 0 cl. There are no significant variables l 2 The regression output below shows the estimated relationship between Price and the independent variables Curb Weight, Horsepower, and 10 11 Acceleration. If performing a test for Overall Significance for this model, I I what is the test statistic's value? ANOVA _ Significance F Finish attt Intercept 479.97 112.86 Acceleration 3.14 1.30 Select one: Q a. 0.54 O b. 14.16 O c. 4.70 Q d. -O.85