7. A fundamental distinction between trend projection and linear regression is that: (1 point) a. trend projection uses least squares while linear regression does not b. only linear regression can have a negative slope. fc.) in trend projection the independent variable is time; in linear regression the independent variable need not be time but can be any variable with explanatory power. d. trend projection can be a function of several variables, while linear regression can only be a function of one variable. e trend projection uses two smoothing constants, not just one 8. A small family-owned restaurant uses a seven-day moving average model to determine manpower requirements. These forecasts need to be seasonalired because each day of the week has its own demand pattern. The seasonal Indices for each day of the week are: Monday 0.445; Tuesday 0.791; Wednesday 0.927, Thursday 1.038, Friday 1.422: Saturday 1.478; and Sunday 0.903. Average daily demand based on the most recent moving average is 194 patrons. What is the seasonalized forecast for Friday? (1 point) a. 86 b. 136.42 c. 276 d. 27.75 e. 153 9. In a regression equation where y-hat is demand and is advertising, a coefficient of determination (R2) of .70 means that 70% of the variance in advertising is explained by demand. (1 point) a TRUE b. FALSE 10. Suppose that you are using the three-period simple moving average method to forecast sales, and sales have been increasing by 10% every period. Then your forecasts will be lower than the actual sales. (1 point) a. TRUE b. FALSE Answer the three questions based on the case. The chicken brothers own and operate a chain of 12 Los Pollos Hermanos fast food restaurants in United States. The regression output for sales figures and profit is provided below. Sales are given in millions of dollars, profits are in hundreds of thousands of dollars. The chicken brothers owns and operates a chain of 12 Los Pollos Hermanos fast food restaurants in United States. The regression output Sales figures and profit is provided below. Sales are given in millions of dollars: profits are in hundreds of thousands of dollars. SUMMARY OUTPUT Regression Statistics Multiple R 0.868720126 R Square 0.754674657 Adjusted R Square 0730142122 Standard Error 5.1495267 Observations ANOVA of F Significance F 0.000245342 30.7622 Regression Residual Total 1 10 11 SS MS 815 701143 815 7404 25 1262523 26 51753 OO 9166 Coefficients Standard Error Stor P.vale Lower 95 U pper 9 Lower 95 0% Upper 95.0% 5935683364 2 4721133 1.83072 0.0970561 413656 115978039 - 1 2413666 1315978029 1420531819 02561192965546368 0.00025 0. 1494 1 9912012040952494 1991201204 11. Build a regression model to predict the profits of Los Pollos Hermanos fast food chain. 12. What is the magnitude of the relationship between profit and sales? What conclusion do you reach? Explain 13. What would be your forecast of profit for a store with sales of $24 million? (2 points)