Import the data into SPSS and produce a suitable graph to investigate the relationship between the two variables, and report your findings.

For this coursework you are required to solve a regression problem using SPSS. Your solution should be word-processed and submitted electronically. Your solution should include any output produced from the analysis, and a detailed account of the methods you have used, the reasons you have chosen those particular methods, and the conclusions you have drawn.

The problem:

Analysts for an ice cream manufacturer are aware that sales of their ice cream increase when the weather is warmer, and would like to determine the relationship between temperature and sales more precisely. They collect daily data on temperature (degrees Celsius) and sales (thousands of pounds) for six weeks. These data are in the Excel worksheet Ice cream.

Import the data into SPSS and produce a suitable graph to investigate the relationship between the two variables, and report your findings.

Perform an appropriate regression analysis in SPSS, to predict sales figures given the temperature, and write a detailed report of your findings. Your report should address (but not necessarily be confined to) the following questions:

(a)What percentage of the variation in ice cream sales is accounted for by your model?
(b)What is the equation of best fit, and how do you interpret the coefficients in your model?

(c)By how much, on average, can we expect sales to increase if the temperature rises by 5 degrees?
(d)What assumptions are made about the distribution of the data. If you are able to test whether the assumptions appear to be true, report on your results.

(e)On average, what level of sales can we expect on a day when the temperature is 23 degrees?
(f)In a worst case scenario, what is the lowest level of sales that we would expect on a day when the temperature is 23 degrees? (Use a confidence level of 95%.)