Lobster industry 2008, revisited. In Chapter 17, Exercise 53 predicted the annual value of the Maine lobster industry catch from the number of licensed lobser fishers. The lobster industry is an important one in Maine, with annual landings worth about $300,000,000 and employment consequences that extend throughout the state’s economy. We saw in Chapter 17 that it was best to transform Value by logarithms. Here’s a more sophisticated multiple regression to predict the logValue from other variables published by the Maine Department of Marine Resources

(maine.gov/dmr). The predictors are number of Traps

(millions), number of licensed Fishers, and Water Temperature ( F).

a) Write the regression model.

b) Are the assumptions and conditions met?

c) Interpret the coefficient of Fishers. Would you expect that restricting the number of lobstering licenses to even fewer fishers would increase the value of the harvest?

d) State and test the standard null hypothesis for the coefficient of Water Temperature. Scientists claim that this is an important predictor of the harvest. Do you agree?

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Dependent variable is: LogValue R squared = 97.4% R squared (adjusted) = 97.3% s = 0.0782 with 564 = 52 degrees of freedom Source Sum of Squares df Mean Square F-ratio Regression 12.0200 3 4.00667 656 Residual 0.317762 52 0.006111 Variable Coeff SE(Coeff) t-ratio P-value Intercept 1.70207 0.3706 4.59 <0.0001 Traps (M) 0.575390 0.0152 37.8 <0.0001 Fishers -0.0000532 0.00001 -5.43 <0.0001 Water Temp -0.015185 0.0074 -2.05 0.0457