# Managerial report

#### MANAGERIAL REPORT

Roughly examining the data we can say that the relationship between the sales and the advertising is looking to be related as the increase in the advertising expenses relevantly increased the sales but not in a manner. The graphical representation of the data may precisely help us to compare. A bar chart is a simple graphical tool to represent and compare data from which we can say about the relationship between two data. We can also say about the shape of the distribution. The representation of the sales and advertising expenditure data is as follows.

#### Fig 1.1 Bar chart

From the bar graph, we can approximately say that there is a proportional increase in sales as the advertising expenditure increases. So we recommend increasing the advertising expenditures in a steady manner to increase the level of sales.  At the same time, it will cause a reverse result also. If the sales are affected by any other reasons like economic crisis, the increase in the advertising expenditure will not help. So a precautionary plan must be done to increase the advertising expenditure. It is better to increase it while the purchasing power is high in the market. Also, a bar graph is not a sufficient tool to conclude, and let us look at the other descriptive tools. The other similar and powerful graph tool is a frequency polygon which shows the shape of the distribution as primary. The frequency polygon for the sale and advertising data is as follows:

#### Fig1.2 Frequency polygon

From the frequency polygon, we agree with the results of the bar graph and one more observation is that there is a steady increase in the advertising expenditure but an unsteady increase in sales. This shows that the advertising expenditure may not contribute to a consistent sale here. Now let us move on the descriptive data analysis where we can interpret the results more precisely and accurately. The descriptive statistics are the type of statistics where the data are analyzed by the two main measures namely the measure of central tendency and the measure of variation. The important measures of central tendencies are the mean, median, mode, and quartiles. The important measures of variations are the variance, standard deviation, and quartile deviation. The drawback of these measures is that we cannot get any information about the relationship between two data. For that, we have to perform tasks like correlation and regression. First, we do individual analysis and then relationship analysis. Let us find the important measure of central tendencies Mean as the other measures may not help this analysis.

Formula: “  = ” (Weisstein, Eric W)

Mean is the average of the data which is found by dividing the sum of the data with the number of the data. Let us tabulate the data so as to perform the calculations simple.

Mean Sales = 208 / 5 = 41.6 (\$1000s)

Mean advertising expenditure = 35 / 5 = 7(\$1000s)

The mean sales over the period 2004 – 2009 are 41.6 (\$1000s) and the mean advertising expenditure is 7(\$1000s). There will be no information about the growth or decline in the mean. We can decide whether to maintain the average advertising expenditure to maintain average sales. The other major drawback of the measure means is that it does not give the details about individual data and is not robust of extreme values. To overcome these problems the measures of variation will help us. The measure of variation is the measure of the variation of individual data from the mean. The important measure of the variation is the Standard deviation which is the square root of variance.

Standard deviation:

Formula = s = “SN  = ” (Weisstein, Eric W)

#### CONCLUSION

We advise Karen to keep improving the advertising campaigns in better methods year by year to keep the sales higher. The statistical techniques used are deterministic and hence descriptive. A better forecast can be used by inferential statistics. “Shortcomings, weaknesses, and limitations are admitted when the arguments are presented. Dealing with both the positive and the negative suggests objectivity”.

## Reference

1. Kenneth F.Harling(2009), Writing a Managerial report,   The Maple leaf conference, [Online]. Available at http://info.wlu.ca/~wwwsbe/MapleLeaf/Report_Writing_c.html [Accessed: 18th April 2009]
2. Kenney J F and Keeping E S, “Linear Regression and Correlation”. Ch.15 in “Mathematics of Statistics”, Pt.1, 3rd ed. Princeton, NJ: Van Nostrand, pp. 252 – 285, 1962.
3. Weisstein, Eric W., “Mean” From Mathworld – A Wolfram Web resource. [Online]. Available at http://mathworld.wolfram.com/Mean.html [Accessed: 19th April 2009]
4. Weisstein, Eric W. “Standard Deviation.” From the Math world –    A Wolfram Web Resource. [Online] Available at http://mathworld.com/StandardDeviation.html [Accessed: 19th April 2009]

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