BUSINESS STATISTICS

      Task 1. Coursework Brief (total 30 mark and each question 5 mark) For this coursework task you are required to perform an independent samples t-test using SPSS. Your solution should be word-processed and submitted electronically. Your solution should include any output produced from the analysis, and an account of the methods you used to obtain that output. Problem description: 150 students, selected at random from the students studying Business Management at Level 1 in Welsh universities, took part in an Entrepreneurship Project and were marked on a scale of 0 to 100. They were also asked to record whether they had studied Business at A-level or equivalent standard before entering university. Our analysis is carried out with the expectation that those who have studied Business previously will have an advantage in the project. The data are in the SPSS Entrepreneur.sav file. Perform a suitable independent samples t-test on this data. You should address the following questions, explaining your answers in detail: (a) What is the population from which this sample was drawn? (b) In order to apply the t-test, what assumption do we make about the distribution of the data? (c) What is the null hypothesis for the t-test? (d) Do we reject or fail to reject the null hypothesis for the t-test? – Explain why. (e) Is it appropriate to use a one-tailed or two-tailed test here? – Explain why. (f) What overall conclusion can we draw from this output? – include a reference to the minimum difference between the marks of students who have or have not studied Business at A-Level that you would expect to find in the population. Task 2. Coursework Brief (total 30 mark and each question 5 mark) For this task 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. Problem description: Analysts for an icecream manufacturer are aware that sales of their icecream 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 SPSS Icecream.sav file. 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) Ina“worstcasescenario”,whatisthelowestlevelofsalesthatwewouldexpect on a day when the temperature is 23 degrees? (Use a confidence level of 95%.) General key marking criteria include: Accuracy of the calculations Appropriateness of the methodology Clarity and conciseness of the descriptions of the methodology