Datanalyses

Table of Contents

Introduction

Methodology

Statistical analyses

Summary of the information

Assessment of sales performance

Investigation of factors affecting sales

Conclusion

Recommendations

Introduction

Slender Vision Ltd (SVL) is a large company selling Flat screens for computers. It has many shops throughout the United Kingdom (UK). Most of the shops are located in the regions: North, South and East of the UK. There are a total of 105 outlets.

Three types of screens are predominately sold (Type A= 12inches, Type B= 15inches and Type C= 19inches).

Methodologies

The data was analysed using the software package Minitab, version 13, which is designed to make data analysis easier.

The first step was to create an extra column Ð''C10' to hold the total sales figures Ð'- for each outlet, as this was to make it easier to see which outlets were performing well.

Descriptive statistics were used to provide summaries of the information, which makes it easier to compare and analyse different types of data. Correlation and regression was another useful feature of Minitab, which was applied to see which factors may affect the total sales and to what extent. For example, it would be viable to look at the experience of the managers running the outlets, to the sales achieved by that outlet Ð'- so you can see if the more experienced managers obtained higher sales levels, and a strategy could be implemented on the basis of that information.

Statistical analyses

There are three parts to this section:

(i) A summary of the information, for example, how many outlets there are in each region, the mean sales figures for each type of phone etc.

(ii) An assessment of the sales performance for each type of phone to see which generated the most sales in each region, and whether female managers generated more sales than males.

(iii) An investigation of the possible factors affecting sales, for example, advertising expenditure, the years of experience of the managers and the distance of the outlet from the high street.

Variable Count N* Mean SE Mean StDev Minimum Q1 Median Q3

Total Annual Sales 105 0 754,24 9,45 96,87 515,00 679,50 770,00 842,00

Source: SVL

Region Count Percent

North 36 34,29

South 41 39,05

East 28 26,67

N= 105

SVL ltd has the most outlets situated in the southregion (39%), as shown in figure 2 above and the Minitab output (1 = North, 2 = East, 3 = West). The Minitab output displays the Ð''count' as the actual number of outlets in each region, out of 105.

Variable Region N N* Mean SE Mean TrMean StDev Minimum Q1

TYPE A (Ð'Ј000s) 1 36 0 181,03 6,81 182,59 40,88 96,00 150,25

2 41 0 173,22 6,55 174,27 41,95 100,00 128,50

3 28 0 174,57 7,06 175,38 37,37 104,00 138,25

TYPE B (Ð'Ј000s) 1 36 0 253,47 5,45 255,97 32,73 182,00 237,50

2 41 0 251,66 3,61 252,65 23,13 198,00 237,00

3 28 0 245,96 5,42 246,58 28,67 195,00 219,50

TYPE C (Ð'Ј000s) 1 36 0 328,22 7,09 330,47 42,52 236,00 307,00

2 41 0 325,88 7,16 329,84 45,87 180,00 301,50

3 28 0 327,89 7,53 328,81 39,86 252,00 293,25

Variable Region Median Q3 Maximum

TYPE A (Ð'Ј000s) 1 187,00 213,75 250,00

2 175,00 209,50 228,00

3 171,50 211,50 224,00

TYPE B (Ð'Ј000s) 1 265,00 279,50 286,00

2 254,00 269,00 288,00

3 257,50 268,75 281,00

TYPE C (Ð'Ј000s) 1 336,00 364,50 382,00

2 341,00 358,00 384,00

3 339,50 359,50 380,00

The above output shows that overall, the Type C flat screens have the highest value of sales, followed by the Beta phone and lastly the alpha phone Ð'- which is almost only half of the sales of the Gamma phone.

The above output shows that the Gamma phones have the highest Ð''maximum' values in all three regions, with its Ð''minimum' values being almost as high as Beta's Ð''maximum' values. The median value shows that for Alpha, region 1 (North) had the highest value. For Beta, the north, again, had the highest value and for Gamma, region 2 (east) had the highest value. These could be indicators to show which phone is selling best in which region.

Variable Gender N N* Mean SE Mean StDev Minimum Q1 Median Q3 Maximum

12" (£000s) 1 44 0 175.57

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