Causal regression:

Top-Slice is a well-known manufacturer of golf balls. Looking at past sales, they have suspected a certain correlation between demand for golf balls and local weather temperature at any given golfing area. To investigate this relationship, the following data has been collected for a certain location:

Month	Monthly Sales	Avg. Temperature
March 2017	4670	52
April	5310	58
May	6320	69
June	7080	75
July	7210	83
August	7040	82
September	6590	78
October	5520	65
November	4640	54
December	4000	48
January 2018	2840	41
February	3170	42

a) Plot the above data and decide if a linear model is reasonable.

b) Develop a regression relationship: what is the intercept and what is the slope?.

c) What is the model's correlation coefficient and coefficient of determination?

d) What is the standard error of the estimate?

e) Use the regression model to forecast the demand for June and July 2018, when the average temperatures are expected to be 76 and 82 degrees, respectively.