QUESTION 6 Consider the 11-day sample data for an icecream truck business shown in the following table. Price = Per unit price of ice cream Temperature = Average temperature during the day Sales = Total number of units of ice cream sold Price Temperature Sales 2.80 59 23 3.00 54 26 2.00 70 33 2.60 62 33 2.40 63 36 2.20 73 37 1.60 85 38 1.80 81 39 1.20 100 42 1.40 91 44 1.00 98 55 Estimate a multiple linear regression model that predicts Sales (Y) from Price (X1) and Temperature (X2). Regression ANOVA results suggest that O There are exactly two significant predictors in the regression model There is at least one significant predictor in the regression model O There is exactly one significant predictor in the regression model O There is no significant predictor in the regression modelQUESTION 7 Consider the 11-day sample data for an icecream truck business shown in the following table. Price = Per unit price of ice cream Temperature = Average temperature during the day Sales = Total number of units of ice cream sold Price Temperature Sales 2.80 59 23 3.00 54 26 2.00 70 33 2.60 62 33 2.40 63 36 2.20 73 37 1.60 85 38 1.80 81 39 1.20 100 42 1.40 91 44 1.00 98 55 Estimate a multiple linear regression model that predicts Sales (Y) from Price (X1) and Temperature (X2). Regression results suggest that O One unit increase in Sales is associated with about 18 units decrease in Price O One unit increase in Sales is associated with about 18 units increase in Price O One unit increase in Price is associated with about 18 units increase in Sales O One unit increase in Price is associated with about 18 units decrease in SalesQUESTION 8 Consider the 11-day sample data for an icecream truck business shown in the following table. Price = Per unit price of ice cream Temperature = Average temperature during the day Sales = Total number of units of ice cream sold Price Temperature Sales 2.80 59 23 3.00 54 26 2.00 70 33 2.60 62 33 2.40 63 36 2.20 73 37 1.60 85 38 1.80 81 39 1.20 100 42 1.40 91 44 1.00 98 55 Estimate a multiple linear regression model that predicts Sales (Y) from Price (X1) and Temperature (X2). Regression results suggest that O One unit increase in Sales is associated with about 0.27 units decrease in Temperature O One unit increase in Temperature is associated with about 0.27 units increase in Sales O One unit increase in Temperature is associated with about 0.27 units decrease in Sales O One unit increase in Sales is associated with about 0.27 units increase in TemperatureQUESTION 9 It is possible for the Adjusted R square value to be negative. O True O False QUESTION 10 R square always ranges between and O 0%, 1% 0%, 50% O 0%, 100% O -100%, 100%