Essay Sample on My Applied Managerial Statistics Experience: From Fear to Surprise

Introduction

Throughout my elementary school, any course related to statistics would always scare me. Most of the time, my mind was pre-occupied with the notion that any course of statistics was challenging to crack. More so, the comments I would hear from other students were that applied managerial statistics was a tough course where the majority of students fail thus undertaking a lot of re-takes. However, I have been surprised that the case does not apply to my side. I believe the simplicity in this course in our college is coupled with the eloquent design of the course outline as well as the commitment of the tutors to ensure we transition through various topics with ease by engaging students appropriately. Moreover, the practical session was beneficial but at the same time, breathe taking (Siegel, 2016). However, integration of the statistical techniques in the field is a whole new thing that may be new and different from the rest.

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There was also another pre-conceived false notion that the course entails complex and technical formulas that are hard to comprehend. However, I realized a different case throughout this course. It has not been an easy task because the course content is not worthy of a joke. But through the discussion with peers to whom we share similar goals, virtually everything has been manageable. The course content can be so hard on you that you devalue the essence of regular reading and revision. As much as the formula and concepts seem complicated at a glance, with the help of the tutor, the formulas are broken down, and ultimately I used to enjoy grasping the concepts without much straining.

Applied managerial Statistics entails the practical approach of using the statistics in collection, organization, analysis, interpretation, and presentation of the data essential for the operation of the organization (Ewart, Ford & Lin, 1982). The experience I have had in partaking the course is more than what I had anticipated. Applied managerial statistics is a motivating and entertaining program. In most of the course work, the outline does not reflect how the concepts apply to benefit us in real life. I expected to learn the practical aspect of the course and how I can apply applied managerial statistics in the workplace. However, after intensive analysis, I discovered that statistics is not about accepting the face value of the data presented, but is it about interpreting the data to find the context of information to determine its authenticity. Therefore, this course has helped to boost my confidentiality to analyze raw data in statistics so that I arrive at more informed conclusions.

The statistical methods apart from being beneficial in application part where it is used in the field of work, it has as well been crucial in research methodology as well as in making important research decision (Siegel, 2016). The knowledge of statistical analysis methods enables me to be in a position to have a broad approach towards analysis of the data presented in the research (Weerahandi, 2013). To this respect, therefore, it has been possible to manipulate the data and interpret it in every way possible, even to the extent of determining the presence of a relationship between the various groups of data presented (Gaur & Gaur, 2009).

Conclusion

Knowledge of the advantages of the statistical analysis methods has been at the forefront of the determination of the appropriate statistical method of choice to apply (Weerahandi, 2013). Through the determination of the relation between the statistical data, the conclusion can be drawn with a high degree of confidence (Gaur & Gaur, 2009).

References

Ewart, P., Ford, J., & Lin, C. (1982). Applied managerial statistics. Englewood Cliffs, N.J.: Prentice-Hall.

Gaur, A., & Gaur, S. (2009). Statistical methods for practice and research. Los Angeles: Response.

Siegel, A. (2016). Practical business statistics. London: Academic Press.

Weerahandi, S. (2013). Exact Statistical Methods for Data Analysis. New York, NY: Springer.