Interpretation of BMI Data With Excel Analysis Tools
Guided by QTI Data Analysis instructions (Barrera S. 2014) and Don Wardell youtube video instructions (Wardell D. 2014) I selected the range of BMI data for men and women, checked the appropriate desired input from the analysis dialog box in Excel Data Analysis Tool and performed a descriptive statistics as instructed. . According to Central Limit Theory (CLT), for a sampling size greater than 30, from a nationally distributed normal population, the distribution of sample mean can be used as an unbiased estimator of the population mean (Triola, M. M., & Triola, M. F., 2006 p274).Since the number of samples are greater than 30 (n=40), and an assumptions that the distribution is precise (no significant spread or outliers within the range of samples) the requirements of a normal distribution was satisfied.The descriptive statistics summary report of BMI as contained in the Excel Summary shows that national mean or average BMI for men compared to women are 25.998 and 25.745 respectively. Therefore, men have a greater mean body mass index compared to women based on the sampled population.
The men and women confidence level numbers (CLN) as obtained from the statistical summary are 1.468 and 2.64 respectively. Using their respective CLN, men or women respective confidence level numbers are added or subtracted to their respective mean BMI to get the national expected or standard BMI interval limits for both classes. The distribution standard error, for men is .543 (SD=3.43) while the standard error for women is .97 (SD=6.17). The variance of 11.78 for men and 38.1 for women indicates that there is more variability in women’s sample compared to men’s sample. This indicates that a representative sample data collected from the women’s population is less precise than the sample from men’s population in estimating the population parameters. This confidence level assures me that the population mean will lie within plus or minus two standard deviations of the probability distribution
Both (men and women) BMI probability distribution curves are negatively skewed to the left indicating that the distribution has a longer left-hand tail. However, the women data distribution has a wider spread compared to the men. The peakness or flatness of both distribution curves relative to the normal distribution is measured by the term Kurtosis. Women probability curve kurtosis is 1.52 compared to -0.136 for men, hence women distribution curve have a higher peak compared to a flatter distribution or -0.136 kurtosis for men. Based on the Excel summary statistics numbers, the upper and lower confidence BMI limit for men is plus or minus 1.468 BMI. This means that the normal men’s national BMI standard is expected to lie between 24.53 and 27.47 BMI. For the women the normal national standard BMI after adding or subtracting its 2.64 confidence number to the mean BMI will fall between 23.10 and 28.38 BMI. Comparison of the nation BMI standard limits to my BMI value shows that my BMI of 29.5 is above the national BMI standard limit (US Center for Disease Control [CDC], 2014). Based on national studies, US Center for Disease Control (CDC) considers BMI
