Assignment #3 BADM3400 - Business Administration Past Paper PDF

Assignment \#3 -- BADM3400 A **B** B -- --- -- -------- -- --- B B B B A B D D A C C A B A B D C D C D **B-** C A...

Assignment \#3 -- BADM3400 A **B** B -- --- -- -------- -- --- B B B B A B D D A C C A B A B D C D C D **B-** C A **A.** Response Variable: Candy bar sales **B.** r = Σ\[(xi - x̄)/sx\]\[(yi - ȳ)/sy\] / (n-1) = Coefficient of correlation (r): r≈−0.972r \\approx -0.972r≈−0.972. There is a strong negative correlation between price and sales, meaning as the price increases, sales tend to decrease. **C.** Coefficient of Determination (r²): (-0.97)² = 0.94. This means that approximately 94% of the variation in candy bar sales can be explained by variations in price. **D.** Least Squares Regression Line: The slope (b) = r(sy/sx) = -0.97 \* (35.83662/0.56290) = -62.38. The y-intercept (a) = ȳ - b \* x̄ = 70.61538 - (-62.38) \* 1.90385 = 189.22. Therefore, the equation is: Sales = 189.22 - 62.38 \* Price **E.** Estimated candy bar sales if the price is \$4.20: Approximately −71.47 This result is likely outside the meaningful range of the data, suggesting sales would be very low at this high price. **F.** Sales Estimate at \$1.18: Sales = 189.22 - 62.38 \* 1.18 = 115.68. This is a more reasonable estimate as 1.18 falls within the observed price range **G.** Residual when the actual sales are 53 and the price is \$2.20: Approximately 0.710.710.71. The predicted sales were close to the actual sales, with a small residual of 0.71. ​ - - - - - - - - - - - -