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LO2. Analyse realistic management problems based on analysis of data sets and case materials.

Post Date: 12 - Dec - 2019

Faculty of Business and Law Assignment Brief

Text Box: Module Title:                            Business Management Statistics
Module Code:                                          107SAM
Assignment Number and Weighting       CW 2 (50%) Resit
Assignment Title                                     Coursework 2

Assignment Information

Module learning outcomes being assessed:

LO1. Apply basic probability and other quantitative techniques in a business context.
LO2. Analyse realistic management problems based on analysis of data sets and case materials.
LO3. Apply the techniques studied to interpret and communicate findings on data analysis.

This assignment is an individual assignment.

Your coursework consists of the following three tasks with tasks 1 and 2 based on the results of a survey. Some similar tasks will be performed in seminars with the tutors’ guidance. However, some parts of these tasks will require independent study.

As well as submitting the coursework as a word report for all three tasks you MUST also submit an excel spreadsheet containing the analysis which you have used in your word report. 

Task 1

The file “Resit_Survey_Data.xls” contains the data of an anonymous survey. Click on the red triangles, within the spreadsheet, to see details of each variable.

The purpose of this report is to:

• Describe the sample

• Investigate whether factors such as gender, type of student and age influence the type of type of accommodation students stay in during term time.

The report should contain quantitative information, summary statistics and appropriate charts and tables.

The marking scheme is as follows:

• Report Structure and Presentation

o Introduction and summary

o Structure, layout, use of spell checker, charts and tables in text

o Conclusion

• Analysis

o Description of the data.

o Investigation of factors affecting choice of term time accommodation.

Task 2

A company wishes to understand how sales are influenced by the price of its product. To do this, the company randomly chooses 12 UK cities and offers the product at different prices. The results are shown in the table below:

City

Price (£)

Sales

London

2.24

100

Birmingham

4.63

88

Manchester

3.41

94

Derby

3.54

84

Edinburgh

6.22

56

Glasgow

7.12

49

Cardiff

4.76

76

Belfast

7.52

34

Portsmouth

4.21

79

Bristol

6.29

46

Leicester

4.92

80

Newcastle

5.17

63

1. Conduct linear regression analysis.
•  Perform, using Excel, Data Analysis Pack, Regression function, the regression analysis.
2. Produce the scatterplot including a fitted regression line.
3. Write the regression equation using the results of the excel table.
4. Determine and interpret the slope
5. Determine and interpret the intercept.
6. Determine and interpret the R-squared value.
7. Give predictions for volume of sales when the price of the product is set to:
  • £3.50
  • £5.80
8. Explain why the predicted sales volume in question 7. above is just an estimate

Task 3

A company wants to determine the relationship between the company’s advertising expenditure and its sales revenue. If the relationship is a strong one, then the company will be able to forecast the sales revenue for a given advertising expenditure. The following data has been collected over the last nine years. Use the table to answer the questions:

Advertising (£000`s)

Sales (£000`s)

10.85

50.234

20.55

80.997

17.18

86.363

15.99

84.016

13.58

75.381

12.28

56.342

24.76

98.123

19.72

92.489

23.63

102.249

Using the table above answer the following questions:
1. Using sales as the dependent variable, conduct linear regression analysis.
2. Generate the scatterplot of the data with a trend line.
3. Write the regression equation that best fits the data.
4. Determine & interpret the slope and the intercept. Give your answer to 2 decimal places.
5. Using your analysis estimate the sales revenue when advertising is:
  • £14,000
  • £17,500
6. Which variables are statistically significant to your model? Give reasons for your answer
.

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