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17. SSE can never be a. larger than SST c. equal to 1 b. smaller than SST d. equal to zero 18. A regression analysis between sales (in S1000) and price (in dollars) resulted in the following equation Y 50,000 -X The above equation implies that an a. increase of $1 in price is associated with a decrease of $8 in sales b. increase of $8 in price is associated with an increase of $8,000 in sales c. increase of $1 in price is associated with a decrease of $42,000 in sales d. increase of $1 in price is associated with a decrease of $8000 in sales Exhibit 12-6 Dependent Variable 20 25 32 43 Independent Variable 12 19. Refer to Exhibit 12-6. The slope of the regression equation is a. 120.348 b. 12.1965 c.-2.5435 d. 2.5435 Refer to Exhibit 12-6. The y intercept is a. 120.348 b. 12.1965 c. -2.5435 20. d. 2.5435

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Step 1/1

17) SSE can never be

The correct answer is:

a. larger than SST

Explanation:

Since SSE represents only the unexplained variation, it can never be larger than SST, which represents the total variation in the data. SSE can be equal to or smaller than SST depending on the goodness of fit of the model. SSE will be equal to SST if the model perfectly fits the data (i.e., all the variability in the data is explained by the model), and SSE will be smaller than SST if the model provides a good fit to the data (i.e., explains a significant portion of the variability in the data).

Final Answer

the final answer is:

17) option a

18) option a

19) slope = 2.5435

20) intercept = 12.1965

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