Descriptive Statistics - Case Study Example

Critique of the Report on the Effectiveness of the New Drug for Pro Cancer The following is a review on the article that reported on the effectiveness of the new drug for prostate cancer. This review will show that the research team made critical errors in interpreting the statistical information that it was able to derive using the data found in Table 1. Table 1. Number of weeks the patient lived after taking the drug Patient Number No. of Weeks 1 3 2 5 3 6 4 6 5 8 6 8 7 9 8 9 9 9 10 10 11 11 12 45 Figures in Table 1 represent a data set with a mean of 10.

75 and a standard deviation of 11.02. This indicates that with the new drug, the patients lived longer on the average, reaching up to 10.75 weeks of living (Creswell, 2003). This would look like a promising finding because it is higher than the current trend on the mean number of weeks that a prostate cancer patient lives after receiving a confirmed diagnosis of being in stage 4 which is 9.6, with a standard deviation of 3.2. Unfortunately, the data contains an extreme point in this instance, which is 45 and this would certainly draw the mean upwards (Doty, 1996), thereby misrepresenting the behavior of the data.

It can also be observed that the standard deviation is unusually high, and since it measures the approximate distance of the data values from the mean (Black, 2010), this indicates that the data set is highly variable. In order to provide a more appropriate interpretation of the behavior of the data, the research team may choose to eliminate this extreme point. This is usually done when a data set contains a minimum number of extreme values that affect the results when the mean is used to interpret it (Fink, 2003).

Based on the new calculations made once the value of 45 is removed, the data set will now have a mean of 7.64 and a standard deviation of 2.4. Clearly, such results are lower than the current trend. Another “remedy” that may be explored by the research team would be the use of the median instead of the mean in finding the data’s central tendency. The median simply looks at the middle value of the data and is very minimally affected by extreme points (Black, 2010). If the median is used, then the data will result to 8.

5 weeks that the patient lived after taking the drug, and this is again quite lower than the current trend. With these findings, it is clear that the new drug does not provide the results that it promises. There were grave errors in interpreting the data and as such, these interpretations may not be used as a basis in determining the effectiveness of the new drug. References Black, K. (2010). Business Statistics: Contemporary Decision Making. Hoboken, NJ: John Wiley & Sons. Creswell, J. (2003).

Research design: qualitative, quantitative, and mixed method approaches. Thousand Oaks, CA: Sage Publications, Inc. Doty, L. (1996). Statistical process control. Industrial Press Inc. Fink, A. (2003). The survey kit: How to sample in surveys. Thousand Oaks, CA: Sage Publications. References Berg, K., & Latin, R. (2008). Essentials of research methods in health, physical education, exercise science and recreation, (3rd ed.). Baltimore, MD: Lippincott Williams & Williams. Bluman, A. (2004). Elementary statistics: A step by step approach, 5th ed.

McGraw-Hill. Kazmier, L. (2004). Schaum's Outlines: Theory and Problems on Business Statistics (4th ed.). USA: McGraw-Hill.