Lobster industry 2008, part 2.

In Chapter 17, Exercise 54 predicted the price ($/lb) of lobster harvested in the Maine lobster fishing industry. Here’s a multiple regression to predict the Price from the number of Traps (millions), the number of Fishers, and the Catch/Trap (metric tonnes).

a) Write the regression model.

b) Are the assumptions and conditions met?

c) State and test the standard null hypothesis for the coefficient of Catch/Trap. Use the standard -level of .05 and state your conclusion.

d) Does the coefficient of Catch/Trap mean that when the catch per trap declines the price will increase?

e) This model has an adjusted of 94.7%. The previous model of Chapter 17, Exercise 34, had an adjusted of 93.6%. What does adjusted say about the two models?

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Dependent variable is: Price/lb R squared 94.7% R squared (adjusted) = 94.4% - S 0.2703 with 56 452 degrees of freedom. Source Sum of Squares df Mean Square F-ration Regression 68.0259 310 3 22.6753 Residual 3.80006 52 0.073078 Variable Coefficient SE (Coeff) t-ratio P-value Intercept 0.565367 0.3770 1.50 0.1397 Traps (M) 1.30744 0.0558 23.4 <0.0001 Fishers -0.00012 0.0000 -2.94 0.0049 Catch/Trap -9.97788 11.22 -0.889 0.3781 0.3+ Residuals 0.0 -0.3+ -0.6+ 0.75 1.50 2.25 Predicted 3.00