Analyzing Data with SPSS

Working with Descriptive Statistics

The results of the statistical analysis showed that frequency for the two sample populations—men and women—was the same with both achieving a frequency of 1, with one exception being the 68 value for one female participant, whose frequency was 2.68. The range of values was different for the two sample populations: 484 for men and 329 for women, indicating a tighter range in blood sugar levels for female population than for the male population which had a wider range of differences in terms of levels. This finding was also marked in the standard deviation: for men it was 182.03 and for women it was 113.33. The standard deviation tells how far some participants’ levels will stray from the average or mean of the rest of the population. So there is clearly more dispersion among the male population regarding the range of blood sugar levels, at least for the population used in this study.

Statistical analysis is helpful for any quantitative study as it allows for better practice to be achieved through empirical research that can then be applied as evidence-based practice (Lynn et al., 2007, p. 666). This kind of analysis and can be applied to my prospectus as I will be obtaining raw data related to the intervention I will be implementing as is evident in my PICOT. The data can then be analyzed using the SPSS tool and statistical analysis will provide an interpretation of the data for my population just like it did for this population in this practice set (Creswell, 2013; Sullivan & Artino, 2013). This data can then be put into a visual form to help its meaning be more evident for readers, such as a bar graph like in this example in the Appendix.