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Individual written analysis (suitable for a web page) integrating applied quantitative analysis within Excel, real data and focused interpretation. (Maximum words 2,500 with additional evidence as reader notes, data and Excel analysis). 

QUANTITATIVE SKILLS FOR BUSINESS

Description of the assessment

Module Learning Outcomes

On successful completion of the module, students will be able to:

1. Demonstrate knowledge of quantitative techniques for business data analysis.

2. Use relevant quantitative techniques within Excel, with real data to create a focused industry/business analysis. Component 2: COURSEWORK

Summary of Assessment Method:

Assesses Learning Outcomes: 2

Individual written analysis (suitable for a web page) integrating applied quantitative analysis within Excel, real data and focused interpretation. (Maximum words 2,500 with additional evidence as reader notes, data and Excel analysis).

This assessment is an individual client report. You must analyse the data, provided by the Client in the CW2 Excel file. The file contains a sample of companies from the UK food and tobacco manufacturing. You must write a report using your analysis of the data provided, that meet the requirements of the Client as set out below. The data set for this assessment is in the CW2 Excel file in the CW2 folder, in the assessment section of Course Resources. You will also find some notes on the measurement of the variables used in a separate Word file. You are required to analyse the data provided using Excel only. You should use the results of your Excel analysis to create fit for purpose tables and charts, which must be embedded in the body of the report to support your discussion and analysis for the client.

You can submit before the deadline. You should write the report in Word and submit it via the Turnitin link in the Assessment section of Course Resources. Do not submit an Excel file. You will receive individual feedback as comments, summary comments and rubric comments on your report in Turnitin within 3 weeks of the submission date.


Assessment Content

Assessment Requirements

You must write an individual report analysing only the data provided. The data is real UK data from a specialist database. There are more than 5,000 food and tobacco manufacturers registered in the UK, but consistent data on the variables in this data set is only available for the sample you have in the

data set for the latest year available, 2020. The data includes measurements of performance, size, and other variables. The overall aim of your analysis is to help the client understand the UK food and tobacco manufacturing sector. The client is thinking about investing in this sector and wants you to analyse the available data provided in the Excel file. You should use your analysis to provide the client with a better understanding of the performance potential of different groups of companies in the sector. Your report must provide only the analysis that the client has requested, and your discussion must explain why the analysis might be relevant to the client as they think about investing in the sector. Your job is not to decide whether the client should invest or not, or to do financial analysis for the client. Your job is to provide the analysis that the client requests, and provide recommendations drawn directly from the analysis. Only use the data provided. Do not add new or additional data or information from other sources. Only use the techniques we have covered in the lectures. Do not use evidence or techniques that we have not covered in the lectures. You can only use EXCEL spreadsheet for your analysis that we have used in the lectures and/or computer labs.

Any evidence that students have colluded or copied each other or used the work of a source without reference and citation will be investigated and may result in a plagiarism investigation. If you use techniques we have not covered in the lectures, it will be treated as a major failure to meet the requirements of the CW2 brief.

The Client’s Requirements

The client is a business investor. This client has not invested in the UK food and tobacco manufacturing sector before. The client wants you to analyse the data they have provided and present the analysis as a business report of no more than 2,500 (excluding tables, charts, and appendices). The report should help the client in their aim to better understand company performance in the UK food and

tobacco manufacturing sector and how the information from this data set might be used when thinking about investing in the sector. The client has requested the following from you:

The client requires you to provide:

a) An analysis of the distribution of the profit rate across all companies in the data set.

b) An analysis of the distribution of the profit rate, comparing the large and SME (small & medium sized) firms in the data set.

c) An analysis of the distribution of the profit rate, comparing manufacturers in the data set by their export activity.

d) An analysis of the distribution of Return on Capital Employed comparing large and SME manufacturers in the data set.

e) An analysis of the export activity of the manufacturers in the data set against their size, measured by whether they are large or SME companies

f) An analysis of the extent to which the profit margin across all manufacturers in the data set is associated with the other quantitative variables in the data set.

g) An analysis of the extent to which the profit margin for manufacturers in the data set that can be predicted using the other quantitative variables in the data set.

1. In order to meet the client’s requirements, you MUST use all the following methods in

your analysis in the report:

a. Analysis of required variable distributions (using descriptive statistics and histograms) with appropriate explanations and comments on what your findings imply for the Client’s aim.

b. Hypothesis tests of the difference of means with appropriate explanation and comments on what the tests results imply in relation to the Client’s aim.

c. Cross tab analysis with appropriate probability pattern discussion, and associated Chi squared test with explanations of what the results imply in relation to the Client’s aim.

d. Correlation analysis with appropriate explanations of what the results imply in relation to the Client’s aim.

e. Bivariate regression analysis with appropriate explanations of what the results imply in relation to the Client’s aim. The regression output should be reported and the interpretation of the results is required.


Please include all EXCEL output in the appendix.

2. You must choose which techniques and variables to use for each of the client’s stated requirements.

3. Each part of the analysis must be explained. You must say why you chose the variables, why you chose the technique, give appropriate explanations of any results (any calculations should be put in the appendix and not in the body of the report). You need to ensure you interpret the results of techniques used but you do not need to explain calculations to the client. You must provide a full discussion of what your results mean for the client within each part of the analysis (not at the end of the report). Failure to do this will result in very low marks. Marks are mainly awarded for presenting and interpreting the output of Excel for the Client in terms of what it means, not for getting Excel to produce the output. For example, if you say the distribution is skewed, you need to show the evidence and explain why this might be of interest to the client in terms of their understanding performance in the UK food and tobacco manufacturing sector and the client’s plans to invest in the sector.

4. Any tables or charts used must be ‘fit for purpose’ You must adapt the Excel tables and charts so that they meet the client needs and are fit for presentation in a formal business report. When you have done this, you can cut and paste them into the report. Any fit for purpose charts or tables should be put in the body of the report (not in the appendix) and every table and chart should be numbered, with titles, and have beneath it, a full explained and discussion saying what the table or chart shows and how this relates to the client’s aim.

The report must be set out as follows:

5. Write your analysis as a typed report with an appropriate title page, contents page, section headings, numbered and labelled figures and tables, and appendices. You do not need an Executive Summary.

6. You must provide an introduction to your report. Your introduction must state your overall aim and your objectives in order to meet the client’s requirements.

7. You must provide evidence in an appendix showing how you did the analysis and how your results were calculated. Normally this means providing a ‘screen shot’ of part of an excel sheet showing the Excel results. This evidence should be put in the appendix. Do not include a screen shot of all the data.

8. You must provide a conclusion with a summary of your results and recommendations. Your conclusion should summarise what you have already discussed in your analysis, and summarise your recommendations, which should already have been discussed within the analysis. Summarise your findings. Clearly state whether your analysis has met your objectives and why. If you think your report has some weakness, explain what it is and why. Your recommendations must be linked to your conclusions. You will gain marks for this type of critical review.

9. The word count (excluding tables and appendices) is a MAXIMUM OF 2,500 words for the whole report. This report can be well done in fewer than 2,500 words if well written and well focused. You should choose how many words are appropriate for each section in your report. You must provide a word count on the Front Page of the Report.

10. The word count (excluding tables and appendices) is a MAXIMUM OF 2,500 words for the whole report. This report can be well done in fewer than 2,500 words if well written and well-focused. You should choose how many words are appropriate for each section in your report. You must provide a word count on the Front Page of the Report. If you exceed the word limit you will lose marks as follows:

i. 10 marks deducted for exceeding the word limit by up to 250 words

ii. 20 marks deducted for exceeding the word limit by 251-500 words iii. 30 marks deducted for exceeding the word limit by 501-750 words iv. 50 marks deducted for exceeding the word limit by more than 750 words.

11. You should reference your sources. You are not required to read about the UK food and tobacco manufacturing sector. But you are expected to cite sources that relate to your

Excel analysis and statistical techniques. You should cite and reference all materials you use including lecture notes, web pages, on-line books, hard copy books, etc. A citation should be provided whenever you are using a statistical technique. These will include textbooks and web sites. Remember, the client may want to consult a source if they are not familiar with your technique, so a citation in a report can be used to guide the reader to some supporting material. References to sources must be provided using the Harvard method in the text of the report and all sources should be fully identified in a bibliography at the end of the report.

Sensitivity: Internal

2

Sensitivity: Internal

2

Sensitivity: Internal

Sheet1

Profit Margin (%) Number of employees Salaries as a % of turnover Return on Shareholder Funds (%) Return on Capital Employed (%) Cost of production (£) Credit limit (£) SME indicator 1=SME Size 0=Large Exporter 2 = Domestic sales only 1 =Export Sales
0.72 34 4.16 39.1 22.22 23741 5207 1 1
-0.17 7 0.89 -22.97 -14.12 49951 6870 0 2
1.72 153 31.62 10.9 4.36 8067 7421 1 2
0.33 73 19.95 22.01 3.71 9182 8583 1 2
0.57 134 38.68 1.7 1.38 6261 9301 1 2
-2.16 323 27.43 -103.44 -35.98 20874 9398 0 2
-2.16 323 27.43 -103.44 -35.98 20874 9398 0 2
0.07 106 7.89 5.97 0.1 29244 11654 1 1
4.76 71 26.28 218.37 9.19 6330 12868 1 2
-1.69 111 19.37 -30.47 -28.99 10020 14602 1 2
0.45 299 34.34 5.18 1.21 12787 15300 0 2
0.81 118 17.56 3.88 3.01 10863 15615 1 2
-2.54 60 17.39 -8.3 -5.29 6573 16357 1 2
0.68 298 44.05 2.28 1.88 11305 17526 0 2
1.47 12 7.86 22.3 6.1 5170 18508 1 2
-1.66 111 19.37 -30.02 -28.56 10020 19736 1 2
-12.41 44 18.95 -67.28 -48.68 4795 20358 1 2
-0.69 133 18.59 -26.23 -23.34 12558 21470 1 2
-0.24 11 1.13 -10.21 -8.54 52623 21802 0 1
22.42 133 4.14 23.58 22.42 93290 14000000 0 1
1.31 693 5.07 3.18 2.4 1000000 15000000 0 1
26.14 1036 18.54 35.71 42.93 194949 15000000 0 1
-1.38 3622 16.4 -1.96 -0.4 511600 16000000 0 1
3.97 1007 12.19 6.73 6.27 344400 20000000 0 1
54.24 264 9.34 17.18 16.97 91817 20000000 0 1
40.83 942 48.69 27.77 22.03 98700 21000000 0 1
7.87 4460 14.26 29.61 10.88 851600 21000000 0 1
16.16 228 16.4 16.92 15.75 109000 24000000 0 1
2.31 570 1.38 23.96 10.66 5300000 24000000 0 1
6.33 4155 19.94 3.19 4.57 549600 25000000 0 1
28.65 2526 18.23 34.81 11.59 518500 35000000 0 1
19.52 670 12.88 8.22 6.14 184325 38000000 0 1
72.82 128 4.36 21.76 19.57 111300 39000000 0 1
8.59 4255 19.6 4.3 3.84 573700 50000000 0 1
26.62 1649 10.84 8.1 5.81 387871 50000000 0 1
6.55 22200 15.6 11.54 4.6 6100000 50000000 0 1
23.03 3137 13.06 12.51 10.39 853000 50000000 0 1
6.27 3 10.2 20.25 19.87 1000000 50000000 0 1
17.38 27775 11.95 30.17 7.95 4700000 50000000 0 1
6.65 32100 3.33 44.47 11.37 26000000 50000000 0 1
2.5 4 5.59 29.44 29.44 3561 21809 1 2
9.15 72 29.62 13.78 13.51 4083 27346 1 2
-0.66 44 8.94 -13.81 -13.53 24412 27685 1 1
-1.31 113 24.16 -14.76 -13.44 8798 28179 1 2
0.99 207 21.97 8.36 6.08 24349 28186 1 1
1.53 135 27.59 266.83 136.98 4730 28303 1 2
3.24 37 8.15 7.63 4.52 9902 29273 1 2
-5.03 692 16.8 -29.16 -18.92 59166 29927 0 1
0.33 73 19.87 6.16 2.59 9182 31508 1 2
1.23 354 34.1 20.84 11.38 15067 32861 0 2
3.85 5 0.41 26.94 26.94 5124 33246 1 2
0.85 137 19.83 15.72 1.13 13051 33258 1 2
-0.21 40 6.96 -0.45 -0.41 15668 33808 1 2
0.65 66 11.82 44.43 44.43 24250 34682 1 1
3.37 136 17.91 17.27 4.79 19325 35245 1 1
9.6 24 11.03 44.68 40.55 5805 35880 1 2
-11.69 177 10.36 -233.77 -215.98 51297 37559 0 1
-0.86 81 5.02 -9.24 -8.78 36860 37719 1 1
0.39 184 34.36 3.62 3.29 8532 38867 1 2
-12 341 30.23 -49.44 -49.44 48759 44532 0 1
-2.74 41 10.77 -19.19 -18.54 6998 44669 1 2
1.34 137 23.44 11.17 10.99 11251 47352 1 2
-0.26 56 8.28 -2.87 -1.28 11873 47439 1 2
3.17 156 22.78 321.13 60.96 10257 47847 1 2
4.08 13 7.84 25.96 10.75 5233 50253 1 2
-9.55 60 18.26 -47.05 -47.05 7169 51443 1 2
5.47 15 9.57 15.48 15.17 3799 53160 1 2
1.24 162 16.41 42.78 29.07 23012 56112 1 1
8.27 49 11.55 21.79 21.79 6764 56916 1 2
0.01 119 12.75 0.03 0.02 20446 60121 1 1
1.95 62 5.63 31.53 29.69 48809 62397 0 1
-1.34 68 16.78 -7.04 -7.04 8739 62959 1 2
8.46 165 36.58 17.69 17.69 8135 63925 1 2
2.6 52 19.07 99.43 91.36 13789 64297 1 2
-0.44 92 8.45 -4.73 -3.87 38226 64936 1 1
1.08 301 27 14.75 4.69 22879 65092 0 2
0.77 4 2.97 89.7 84.86 21401 65097 1 1
1.32 90 9.38 18.29 12.4 13236 65238 1 2
1.15 135 24.32 13.18 8.65 14933 65247 1 2
4.65 149 12.05 46.3 24.44 28877 65690 1 1
1.87 32 6.65 21.38 12.99 14087 66249 1 2
-7.47 95 32.74 -31.81 -30.17 6210 66977 1 2
-1.8 162 20.92 -25.11 -17.29 15484 67476 1 2
-2.39 66 23.9 -13.82 -13.82 8226 69185 1 2
8.05 49 10.27 13.93 13.84 11773 69415 1 2
2.33 13 4.07 27.09 12.85 13008 70913 1 2
-0.38 84 19.02 -2.11 -1.62 11054 72877 1 2
2.3 199 30.64 30.45 19.01 14338 73438 1 2
0.46 78 14.04 51.67 3.47 20783 73844 1 1
0.96 159 16.91 2.58 2.48 18185 74613 1 2
2.04 140 20.5 40.12 14.04 12169 75371 1 2
0.04 46 11.55 0.38 0.37 13944 75535 1 2
0.9 20 5.95 19.3 10.45 13949 76103 1 2
-1.14 54 17.77 -3.82 -3.51 7936 76283 1 2
-5.46 82 32.99 -17.62 -11.4 6646 76861 1 2
2.89 74 14.6 133.87 130.57 13009 78000 1 2
0.51 109 29.66 2.1 1.66 8178 79432 1 2
-1.18 135 24.32 -9.63 -6.19 14933 80034 1 2
1.63 254 42.5 382.4 82.74 10023 80543 1 2
0.39 53 9.77 4.14 1.74 19331 81246 1 2
1.42 71 18.3 38.62 25.7 8162 81948 1 2
1.59 72 11.31 24.42 13.13 11293 85356 1 2
2.51 82 19.24 22.87 16.2 9973 86720 1 2
1.17 97 19.68 8.1 7.72 20575 86756 1 1
-3.11 78 21.52 -13.46 -13.46 6647 90772 1 2
1.09 68 14.45 6.73 5.61 14445 91060 1 2
-4.53 343 47.55 -32.43 -24 13283 93233 0 2
-5.94 14 3.68 -46.59 -46.59 16285 93764 1 2
-0.82 42 9.78 -4.28 -3.79 11646 98153 1 2
1.57 12 4.35 7.83 6.27 15343 99105 1 2
1.06 121 16.84 7.48 5.77 16970 101506 1 2
-2.51 130 14.9 -14.11 -13.07 6725 102697 1 2
-1.64 82 24 -5.3 -5.3 7504 103126 1 2
-0.48 9 1.59 -40.86 -2.59 24995 103589 1 1
1.18 248 8.33 17.93 14.02 61349 105655 0 1
1.98 88 5.29 23.36 5.32 22011 106459 1 1
1.71 59 10.13 12.65 11.76 14332 106594 1 2
-1.49 64 11.25 -7.57 -7.57 12261 107215 1 2
1.24 55 19.12 4.39 4.31 6244 108996 1 2
13.84 34 6.24 24.23 24.23 7474 110136 1 2
4.92 28 14.99 14.33 11.81 7748 112524 1 2
0.85 64 4.03 14.74 12.06 40732 112769 0 2
0.29 94 7.46 3.01 2.65 32349 112791 1 1
-3.4 102 43.81 -5.77 -5.51 4598 113629 1 2
5.68 48 19.01 27.06 20.05 6511 114023 1 2
-3.61 305 22.81 -42.22 -18.63 40200 115430 0 1
5.44 97 16.57 58.07 30.14 8815 115962 1 2
0.34 177 15.14 3.9 3.82 25874 117702 1 1
-26.26 77 10.06 -159.27 -154.45 28315 117864 1 1
-1.09 82 17.14 -5.08 -2.84 11679 119209 1 2
1.31 301 21.75 14.2 8.13 32355 120451 0 2
0.82 24 3.58 8.15 7.87 27340 120589 1 1
-0.96 163 24.12 -4.9 -3.3 12735 121363 1 2
13.57 190 25.09 16.12 15.97 10626 121577 1 2
-7.17 692 30.07 -97.19 -71.94 50049 121851 0 1
3.72 74 16.15 20.11 11.2 10504 122371 1 2
-0.14 51 20.51 -0.44 -0.4 7152 122839 1 2
3.72 74 16.15 20.88 11.43 10504 123240 1 2
0.78 354 34.1 4.68 3.62 15067 123764 0 2
5.41 102 17.43 27.64 5.01 8145 125234 1 2
3.46 157 14.22 81.77 72.03 15532 125352 0 2
8.6 13 7.84 92.57 92.57 5233 127408 1 2
2.87 219 35.58 10.11 6.3 7614 128560 1 2
0.79 15 4.28 5.55 5.4 19858 130847 1 2
0.11 88 12.76 0.45 0.4 12930 130927 1 2
-32.09 49 23.42 -37.87 -23.78 5125 132089 1 2
-0.39 53 7.63 -2.36 -1.91 23153 132594 1 1
-9.1 145 19.64 -40.35 -28.52 13809 133692 1 2
0.79 85 19.52 29.74 5.95 9457 133758 1 2
4.63 20 10.68 26.78 26.27 11679 135417 1 2
-2.04 58 11.44 -7.31 -6.14 17686 136593 1 2
-0.3 70 7.25 -3.26 -2.16 26314 137414 1 1
8.33 246 54.45 42.58 14.58 6050 137599 1 2
2.8 78 15.05 23.09 14.48 11863 137827 1 2
-0.79 165 20.42 -3.14 -2.37 19234 138620 1 2
0.8 152 24.91 6.59 3.46 8963 138920 1 2
0.85 41 7.84 5.58 5.58 20814 139477 1 1
1.96 95 4.97 24.78 22.79 36551 139996 1 1
1.24 99 23.35 15.35 5.73 10231 140834 1 2
-5.97 264 31.33 -21.45 -9.69 19751 142914 0 2
2.43 104 6.5 43.89 35.31 23408 144955 1 1
1.23 125 33.15 2.04 1.5 5144 145434 1 2
-1.37 107 33.24 -3.2 -2.69 8618 145499 1 2
2.96 115 11.96 41.98 28.5 18872 145745 1 1
-8.07 55 11.15 -77.66 -71.91 22804 146130 1 1
2.06 353 41.58 12.28 9.59 19325 146382 0 2
-33.91 726 39.2 -20.97 -8.78 40279 147381 0 2
2.35 104 6.5 31.62 26.79 23408 149151 1 1
2.14 64 13.69 8.32 7.65 14332 149983 1 2
2.79 603 34.97 3.76 2.52 9447 150169 0 2
3.3 259 30.63 29.47 18.91 16919 151025 0 2
3.09 147 38.81 22.82 16.47 5968 152649 1 2
0.81 118 17.56 4.02 3.1 10863 152773 1 2
-0.76 192 19.25 -4.15 -3.99 20027 154085 1 1
-4.44 267 21.52 -32.08 -28.71 28316 154263 0 2
1.58 128 25.07 14.1 11.1 9540 155457 1 2
2.96 61 10.59 21.01 20.71 13540 156101 1 2
1.35 460 28.15 11.26 11.26 30229 156421 0 2
5.53 293 36.19 25.14 23.44 6708 156722 0 2
2.2 141 15.9 27.51 26.71 28061 156762 1 1
1.59 138 8.38 16.4 16.31 43609 158102 1 1
2.16 40 10.49 11.06 10.36 17710 160092 1 2
2.07 129 23.81 10.71 9.34 6657 160842 1 2
0.81 50 1.32 370.03 370.03 136857 162546 0 1
4.75 11 3.36 12.71 12.71 10635 162821 1 2
2.76 204 12.49 13.67 11.3 27649 165429 1 1
4.37 74 17.41 14.79 8.13 9720 166414 1 2
-1.76 102 32.09 -4.48 -3.66 7877 166430 1 2
3.26 140 16.67 24.57 3.6 25515 166567 1 1
2.65 62 13.22 28.84 14.56 12485 167123 1 2
2.44 153 15.63 9.57 8.89 17455 171830 1 2
4.2 477 48.2 70.88 21.49 19995 172942 0 2
1.93 30 10.01 16.17 9.23 10977 174941 1 2
0.46 108 10.65 8.43 6.27 35873 176118 1 1
13.67 179 33.34 39.79 39.68 6505 177865 1 2
5.61 66 2.09 47.81 42.74 13966 179160 1 2
-6.58 30 22.93 -16.51 -11.05 4166 179718 1 2
1.68 67 6.37 11.08 10.93 24757 181435 1 1
4.63 15 5.84 10.56 9.58 7813 182400 1 2
0.67 58 11.44 2.82 2.74 17686 184135 1 2
10.37 246 54.45 15.08 14.57 6050 185705 1 2
5.08 71 26.28 8.89 8.55 6330 186193 1 2
1.29 56 22.99 2.72 2.22 4053 188313 1 2
-0.78 306 5.95 -16.78 -14.34 182824 188848 0 1
2.52 186 19.34 13.74 13.25 19502 192878 1 1
4.63 15 5.84 10.56 9.58 7813 192883 1 2
0.02 115 17.79 0.08 0.05 13812 193294 1 2
0.43 85 11.07 2.52 2.44 26742 194565 1 1
1.04 90 28.56 3 1.95 5514 196095 1 2
1.1 125 35.34 1.79 1.44 5280 196813 1 2
1.63 83 12.08 7.99 5.39 17831 196973 1 1
5.26 52 13.93 33.71 32.46 12738 197116 1 2
1.74 179 8.17 6.58 5.72 57903 197172 0 1
10.99 71 38.83 22.65 22.46 5840 198600 1 2
2.98 80 9.77 18.51 15.39 18896 199419 1 2
3.94 43 8.25 17.49 16.41 16906 202564 1 2
-5.62 36 4.3 -35.08 -10.99 35862 202958 1 1
3.26 84 10.44 9.35 7.85 17822 207825 1 2
1.43 39 4.95 9.03 6.88 25083 209618 1 1
3.51 215 23.14 60.41 49.29 17762 211128 1 1
3.55 81 10.25 14.77 14.77 17602 211417 1 2
7.8 67 16.05 23.99 22.65 8263 213255 1 2
2.19 56 10.65 5.38 5.37 10095 216709 1 2
5.68 116 20.23 24.11 15.16 11235 218454 1 2
0.34 675 22.81 4.77 1.37 89475 218466 0 1
5.07 4 1.24 435.79 435.79 23511 221117 1 1
2.91 98 10.89 13.31 13.17 22156 222716 1 1
4.24 275 16.52 13.09 12.83 43098 223230 0 1
0.47 110 15.68 3.58 3.49 19305 223315 1 2
3.76 251 27.63 18.85 18.01 14983 224499 0 2
1.09 143 4.55 17.19 14.82 82744 225523 0 1
-1.34 311 36.89 -34.8 -11.34 17047 226221 0 2
4.61 157 23.76 48.71 38.84 14842 226375 1 2
19.99 16 8.98 23.39 23.36 3290 226747 1 2
-0.44 92 8.45 -1.96 -1.79 38226 226812 1 1
-6.33 121 32.25 -14.86 -9.64 9113 227242 1 2
3.95 215 23.12 37.2 27.19 17762 228030 1 1
6.83 82 13.62 18.8 18.74 12831 228057 1 2
4.51 58 22.94 4.26 3.9 5039 228348 1 2
-0.86 336 45.45 -1.95 -1.67 9472 231426 0 2
-3.53 33 11.78 -3.71 -3.19 5621 231859 1 2
-4.77 182 27.6 -4.42 -4.42 29616 232103 1 1
6.88 105 26.2 16.68 15.53 10722 232467 1 2
4.64 236 24.48 20.59 13.86 13026 233493 1 2
3.7 151 14.91 72.96 72.96 25924 234429 1 1
3.89 130 16.9 33.91 18.72 22149 235219 1 1
4.42 333 33.62 142.73 67.59 23316 237180 0 2
3.82 61 4.4 30.18 16.78 21893 237469 1 1
1.83 126 25.28 6.45 6.08 15825 238611 1 2
-7.99 9 5.39 -10.95 -10.95 8146 242301 1 2
-4.51 103 17.84 -11.33 -10.38 13327 244656 1 2
4.23 23 4.1 14.18 11.07 21352 245444 1 1
4.23 29 8.12 18.81 15.53 22584 245964 1 1
1.48 55 10.03 5.94 5.75 19343 246916 1 2
0.43 178 50.83 0.69 0.57 6211 247027 1 2
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6.91 215 6.95 31.36 30.54 79859 2600000 0 1
15.98 82 8.99 57.33 57.33 45006 2700000 0 1
-4.98 1470 27.99 -13.19 -8.97 124547 2800000 0 1
0.46 958 7.6 3.02 2.26 461292 2800000 0 1
4.7 1085 17.98 13.28 10.43 150329 2800000 0 1
25.02 98 8.59 15.68 15.39 28217 2800000 0 2
6.14 225 3.17 19.18 18.36 192687 2800000 0 1
0.74 1498 20.63 1.94 1.73 157469 2900000 0 1
11.53 667 25.12 9.33 8.03 43688 2900000 0 1
3.8 777 12.68 15.18 13.9 170779 3100000 0 1
2.95 515 6.67 16.71 12.25 293012 3100000 0 1
12.17 194 9.48 27.14 27.14 78843 3100000 0 1
10.24 1265 28.13 45.38 32.14 98322 3100000 0 1
0.85 1697 15.57 2.61 2.07 274605 3200000 0 1
0.84 1504 20.94 3.13 2.61 157469 3200000 0 1
1.62 899 6.96 7.11 6.64 370630 3200000 0 1
1.75 204 8.28 2.39 2.21 107559 3300000 0 1
0.94 3177 28.51 2.92 1.74 210881 3300000 0 1
2.37 2361 22 12.03 10.67 153901 3300000 0 1
3.16 1210 13.2 10.67 7.42 343381 3400000 0 1
1.75 1161 7.01 23.48 11.18 646200 3500000 0 1
4.83 312 15.41 4.87 2.89 73036 3600000 0 1
19.09 85 4.05 24.3 20.72 71919 3700000 0 1
7.33 218 7.18 26.05 25.39 79859 3800000 0 1
5.51 352 12.12 5.46 5.28 69021 4100000 0 1
22.85 323 20.78 10.61 9.25 37536 4100000 0 1
-16.72 7861 29.84 -10.3 -5.05 80644 4500000 0 1
1.27 746 6.13 13.57 9.96 381261 4500000 0 1
1.43 1368 19.33 4.42 1.87 209325 4600000 0 1
1.43 1368 19.33 4.44 1.88 211086 4600000 0 1
2.06 2107 14.98 10.03 9.81 402986 4700000 0 1
8.81 236 17.38 4.64 4.59 42457 4800000 0 1
12.23 463 13.89 27.19 26.15 130249 5200000 0 1
-7.22 1599 24.87 -7.32

Some things to consider for your discussion for the client in CW2

I know that some of you are starting your CW2 so here is some general ideas to think about when you get to the point of writing discussion around your tables, charts, hypotheses tests, etc.

1. Think about your client as an investor, they may have many strategies, don’t assume anything, and don’t tell them what their investment approach should be. An investor might want to pick winners, like an Angel Investor, who puts all their money into one company and wants to work closely with the company. An investor might want to spread their money widely by buying shares in companies across the whole industry. An investor might be looking for riskier investments or safer investments, you don’t know what they want. Don’t assume anything.

2. When you use a variable, make sure you tell the client how it is measured and why it might interest them. For example, clearly both profit margin and shareholder return are measures of potential gains or losses for the investor so they should consider these carefully and that is why they have asked you to look at them. But tell them how these are measured by looking at the notes on the data set.

3. When you are looking at the distribution of any variable, you will be using descriptive statistics and a histogram. So here are some things to consider when looking at any descriptive stats table for profit margin. When you are looking at the ‘mean’ value of profit margin you need to say why it might interest the client. The population mean for profit margin represents the average return an investor might expect if they spread their investment across all firms the sector. Use the confidence interval estimate for this. It is clearly a measure of performance. Whether the value is high or low, depends on what it is compared with, leaving your money in the bank? Investing in another sector? Etc. You also need to say something about the data as a sample from the population. If the client invested in only your sample companies in this sector, they might expect something like the sample mean return, but what if they pick other companies in the sector? Think about what the median shows. Half of the sample firms earn less than median profit margin and half more than that. Is the median the same as the mean? If not, it shows skew. The skew value may shows bunching of profit margin at one end of the distribution. Think about this. If the client only picks a few companies to invest in, are they are likely to get a much lower or higher margin than the average. The sample standard deviation will be useful here. What if the investor wants to try to ‘cherry pick’ very high profit margin firms? Should they expect profits to be the same in every year? This is just one year of data. When you look at the standard deviation, don’t forget to add the coefficient of variation as this is a way of judging whether the variation around the mean is high or low. What would high or low variation imply for an investor? Think about discussing the risk the investor might want to take. Low variation around the mean profit margin implies the investor is more likely to get a return closer to the mean, it is more predictable, lower risk. So, say that the client should consider whether they prioritise looking for low risk with possibly lower return. Explain the client is less likely to achieve the mean return if the standard deviation is high when they pick only a few firms. Maybe the client is looking for this type of higher risk strategy. Don’t make assumptions. Don’t tell the investor what to invest in. That is not your job. Explain what the numbers mean, depending on what type of strategy the client wants to adopt.

4. You can use a confidence interval to estimate the population mean whenever you do descriptive stats. Explain the limitations of making decisions based only on the sample data you have got and why the client needs to think about the pattern in the population of data from the whole sector, which is not available.

5. When you are comparing descriptive statistics by a characteristic like size, you need to explore the differences of central value, spread and skew and what these differences might imply for the client (as above). The client might be considering targeting SME manufacturers or only large corporations. One profit margin might appear higher than the other using the mean and or median, so consider the implications for the client as state earlier. This is a sample, so you must use a t – test to test the difference of means and explain simply why the test is needed, what is tests (hypothesis) and what the result shows for the client. Is the apparent difference in the sample means across these groups likely to be found in the population of data? If you cannot reject the Ho, then you must explain to the client what it means in terms of investing in the sector. Is there likely to be a difference in the spread in the population across these 2 groups and hence what conclusion can they draw about risk of achieving the mean return for their investment if they target one group rather than another. If one group is left and the other is right skew for example, then consider what this says about the chance of getting high or low profit margins in the two sectors.

6. If you find a pattern or if you find no pattern in a cross tab, explore what that means for the client. No pattern is just as interesting as a pattern. Is size related to export activity? Find out and explain to the client why it might be of interest. The investor might prefer large well-known companies, or they might be looking to invest in SMEs. They might like focused companies or companies which export or those that are UK focused. It depends on what they are looking for in their investment portfolio. You don’t know what they want, but clearly, they want to know if these are related or not as they have asked for the analysis.

7. When you look at correlation values (positive or negative) you need to discuss for the client what you find. Is there a simple reason why two variables are correlated positively or negatively? Are the correlations significant. Do the correlation results tell us what affects profit margin? If so, how could the client use that information, if not what does that mean for the client if they are looking for high profit firms?

8. When you look at bivariate regression you need to say something about the method and why you are using it. You need to explain the regression model, say clearly which variable is the dependent variable, and which is the independent variables (with appropriate labels) and look at the data notes and think about what information it gives to the client. You should set these out for the client with a clear statement identifying the variables. When you have your results, you must explain the coefficients of the predicted regression equation, you must explore the equation in full, tell the client how to interpret coefficient values in context in each case and how it might be useful for them. You must test your coefficient values using one of three methods of hypothesis testing (t tests, p-value, or confidence interval) in the results and explain what the conclusion of the test is in each case. You must test the model overall using the adjusted R2. How can the model be used in forecasting profit margin for the client?

9. You need to put ‘fit for purpose’ charts and tables in the body of the report. You can put snapshots from your EXCEL file as evidence of what you did in the appendix. Your report should have a standard business report structure, content page, with numbered sections, numbered and titled charts and tables, (you don’t need an executive summary for this) with appropriate citations to techniques. Follow the instructions in the brief. Read the brief carefully.

Sensitivity: Internal

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