In recent years, fishermen have suffered financial hardship because of shortened fishing seasons, reduced catches and lower market prices. Moreover, fishermen have complained about price fluctuations and have called for a system of minimum prices. One suggestion made was that the size of the catch had an immediate impact on prices, and that this relationship should be clarified before potential solutions were discussed. To investigate this issue, a random 12-week period was selected to study the price of fish versus the average daily catch. The data for the 12 weeks were collected and recorded as follows:

Let x = average daily catch ('00 kg) and y = price per kg ($)

Sum of all x values = 6,970 Sum of all y values = 16.45
Sum of all x-squared values= 4,315,894
Sum of all y-squared values= 24.94 Sum of all xy values= 8,972.8
n = 12
Part (a):
Determine the sample regression line that shows the price per kilogram as a function of average daily catch.
Part (b):
Calculate the standard error of estimate. What does this value tell you about the relationship between the two variables?
Part (c):
Do these data provide sufficient evidence at the 5% significance level to allow you to conclude that large catches result in lower prices?
Part (d):
Calculate the coefficient of determination. What does this value tell you about the relationship between the two variables?