A state fisheries commission wants to estimate the number of bass caught in a given lake during a season in order to restock the lake with the appropriate number of young fish. The commission has information on the seasonal catch (CATCH) in thousands of bass per square mile; the size
A state fisheries commission wants to estimate the number of bass caught in a given
lake during a season in order to restock the lake with the appropriate number of
young fish. The commission has information on the seasonal catch (CATCH) in
thousands of bass per square mile; the size of the lake in square miles (SIZE); the
number of lakeshore residences per square mile (RESIDENCE); the number of living
places for bass (i.e. weed beds, sunken trees, drop offs etc.) (STRUCTURE) and
ACCESS a dummy variable equal to 1 if the lake has public access and 0 if not.
What do you think are the expected signs of the regression coefficients?
Justify your choice.
Using R-studio, estimate the multiple linear regression model. ALL input codes and output tables should be provided.
(b) Is the overall regression equation statistically significant at the 1% level?
Justify your answer. Ensure that you state the null hypothesis(es) and the
decision rule in your analysis.
(c) Find and interpret a 95% confidence interval for the change in the seasonal catch resulting from a one-unit increase in the number of living places for bass, with all other variables unchanged.
Trending now
This is a popular solution!
Step by step
Solved in 2 steps with 1 images
