Refer to Problem 19. Observation 12 corresponds to Dun and Bradstreet. Redo the straight-line regression analysis omitting this observation. Do your conclusions in parts b and d of Problem 19 change? What, if anything, does this imply about the influence of a single observation on a regression analysis when the number of observations is fairly small? Do you think it is reasonable to throw out Dun and Bradstreet? Discuss.
Problem 19
The number of employees (X) and profits per employee (Y) for n = 16 publishing firms are given in Table P-19. Employees are recorded in thousands and profits per employee in thousands of dollars. A portion of the Minitab output from a straight-line regression analysis is given below.
The regression equation is
Profits = 18.0 - 0.271 Employees

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Coef SE Coef Predictor Constant 17.954 4.457 4.03 0.001 Employees -0.2715 0.17261.57 0.138 S= 10.6112 R-Sq = 15.0% R-Sq(adj)= 9.096 TABLE P-19 Firm Profits ($1,000s) Employees (1,000s) 33.5 31.4 25.0 23.1 14.2 11.7 10.8 9.4 6.3 10.7 7.4 17.1 21.2 36.8 28.5 10.7 10 12* 14 9.8 9.1 8.5 8.3 4.8 3.2 2.7 -9.5 70.5 14.8 21.3 14.6 26.8