The Measures of Central Tendency and the Descriptive Statistics

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Table of Contents

Introduction of the study
Drawbacks of the study
Importance of standard deviation
Recommendations and conclusion
References

Introduction of the study

The measures of central tendency like the mean, median, mode that will be discussed in this essay and the descriptive statistics are very useful in summarizing any collected data and help to come up with detailed and correct conclusions. The aim of this essay is to analyze the measures of central tendency and descriptive statistics used and their importance. The essay will also examine the statistical methods and data undertaken for a current research undertaken by Cambridge University and determine how well the statistics fits it. The study looks upon a recent innovation of new treatment proposed for patients in the later stage of prostate cancer. The discrepancy in the statistics collected under this study shows that such results may cause doubts in research findings. According to statistics, the sample of the patients used in the survey was only 12 collected from the age group of 47 to 73. Because of the narrow range that was used in the research, more accurate results were expected. The other view that was shown in the study was that men were the only patients selected for the study. This is seen to have contributed to better results in the study (Plichta & Kelvin, 2001).

Drawbacks of the study

Despite a good descriptive analysis produced by the study, the study never gave out results that were promising with respect to the measures of central tendency. In relation to s of the measures of central tendency, the research team gave out inaccurate results relative to the statistics given. This was based on the existing statistics and the assessment of the data used in coming up with the inferences. With a small sample of size 12 (12 patients used) the results were supposed to be favorable. According to the current study, a mean of 10.75 obtained and it corresponds to the mean of the past study. However, because a small sample size was used and there was significant variation in the figures the mean must be incorrect. This is true since the least is 3 weeks and highest is 45 weeks thus making the use of the mean inappropriate (Elizabeth & Stancey, 2012).

Importance of standard deviation

The calculation of dispersion in any study is more accurate when the standard deviation is used. This arises since the standard deviation has the ability to accommodate the extremes of any given data. For example in the case of the range, since the lowest value is three and the highest value is 45 the range of the data is 42, which is too high. However, that large disparity between the lowest and the highest value within a very small sample size will give wrong statistics. This makes the standard deviation the most appropriate in examining the statistics collected. According to the past statistics, the results of the study by the research team were unacceptable because small sample size was used together with the tapered age group (Alexander, Franklin & Duane, 2001; Plichta & Kelvin, 2001).

Recommendations and conclusion

In the case of such study, the statistics obtained should be invalidated and another study conducted with a large sample size being used. With a large sample size of the patients, the study will yield more precise and appealing results when analyzed. The age difference is widened to accommodate larger sample sizes leading to a more accurate conclusion. There is a need to incorporate other measures of central tendency such as mode and median in the analysis since they give more precise information about the statistics under consideration (Alexander, Franklin & Duane, 2001; Plichta & Kelvin, 2001).

References

Alexander, M.M., Franklin, A.G. & Duane, C.B. (2001). Theory of statistics. Newhill: TataMcGrawHill.

Elizabeth, A.K. & Stancey, P. (2012). Research methods for health care. Web.

Plichta, S.B. & Kelvin, E.A. (2001). Munros statistical methods for Health Research. Brandon hill: Lippincott Williams and Wilkins.

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The Measures of Central Tendency and the Descriptive Statistics

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