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Business Related Problem that Utilizes Statistics

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A synopsis of a business related problem where statistics was used to solve the problem. The synopsis needs to include a discussion of the specific problem, the research methodology used, the quantitative and qualitative tools used, and the benefit and limitations of the resolutions used.

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By example, this solution provides assistance with business related problems where statistics was used to solve the problem. e.g. the specific problem, the research methodology, the quantitative and qualitative tools, and the benefit and limitations of the resolutions used.

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Please see response attached (also below). I hope this helps and take care.

RESPONSE:

This question is straightforward. You will need to locate a business problem and write a 3-4 page paper. Your tentative outline might look something to the effect:

I. Problem definition
II. Research Methodology
III. Methods (e.g., quantitative or qualitative tools, such as surveys, questionnaires, interviews, etc.)
IV. Conclusion/ Discussion (e.g. benefits and limitations).

Let's look at three business problems below, one's that you can perhaps use as exemplars for your own synopsis (don't use these examples though, find your own problem and use as exemplars for format only) or use as a source of generating your own business problem ideas:

Example 1: Problem

Problem

Human resource management has most important role for successful running of the business. With the dearth of skilled labor, the most important role of human resource management is to retain manpower for considerable amount of time .The companies have been appointing beginners and train them on the job. As the company is spending money in training they wish to retain employee for considerable amount of time. The Statistical Analysis Department of ABC Corporation reported that the mean length of time of newly employed individuals in California was 17.00 weeks. A local Chamber of Commerce has commissioned a team to study on the status of employment in the City of Riverside area. As a part of study we (the team) were interesting in investigating and analyzing few factors and following report has been prepared.

Analysis
As part of investigation, the first step would be to pick up a sample. Because of financial constraints it was decided to restrict the sample to 16 individuals in different age group. Therefore, it was decided to restrict the area of study to City of Riverside California. The following data was collected.

Age 55 30 23 52 41 25 42 45 25 40 25 25 59 49 33 35
Weeks
employed 21 18 11 36 19 12 7 25 6 21 13 11 34 27 18 20

The distribution of age was found to be as follows:
Age Frequency
20-30 4
30-40 4
40-50 5
50-60 3

From the above graph we can see that sample had people more or less equally distributed. The people in the age group 40 - 50 are slightly more represented.
Similarly weeks employed is also considered
Weeks employed Frequency
0-10 2
10-20
20 inclusive 8
20-30 4
30-40 2

From the above histogram it can be noted that sample had more people employed between 10-20 weeks.

After the studying the distributions our interest was to develop a 99% confidence interval estimate of the mean age of newly hired employees. The confidence intervals are given by 37.75 + 3.07*2.947 and 37.75 - 3.07*2.947 (37.75 - 9.05, 37.75 + 9.05) = (28.69, 46.81)
From this we can conclude that the mean age of newly hired employees lie with in this range with .99 probability.

Next step would be to test the hypothesis whether the mean duration of employment in Riverside is greater than the California mean duration of 17.00 weeks
H0 =mean duration is 17
H1 = mean duration is > 17
_
Test statistic t = (x - µ)/ s/√n ~ t(15)
Calculated value is t = 18.6875 - 17 /2.26 = .7466
Tabulated value at 1% level of significance is 2.602

From the above analysis, since calculated value is less than tabulated value we accept H0 and conclude that the mean duration of employment in Riverside is equal to 17 weeks.
Next our interest of study is to find if there is any relationship between the age of a newly employed individual and the number of weeks of employment .For this we calculate coefficient of correlation .r = .796 ~ .8. This value indicates that there is strong relation, positive relation between the age of a newly employed individual and the number of weeks of employment .We can say that increase in the age of newly employed the more the number of weeks of employment.

Conclusion

As mentioned at the beginning that lot of money will be spent in training, the companies can use this analysis for their recruitment. Since there is positive correlation the company can recruit people in the age group 40-50 that the mean duration of employment in Riverside is equal to 17 weeks. The companies can even analyze the various ...

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