NR 439 Week 6 Data Results and Analysis

Sample Answer

According to this week’s lesson, the four basic rules for understanding results in a research study are understand the purpose of the study, identify the variables—dependent and independent, identify how the variables are measured, and look at the measures of central tendency and the measures of variability for the study variables. I chose to explore the rule identify the variables-dependent and independent. A dependent variable is something that depends on other factors. An independent variable is a variable that stands alone and isn’t changed by the other variables you are trying to measure.

A dependent factor can be changed by what happens with the independent factor but a dependent factor can never change an independent factor. A simple example would be Insulin causes a drop in blood sugar. Insulin is the independent factor and blood sugar is the dependent factor. There is no way for blood sugar to cause a drop in insulin. “Statistical significance tells us the findings are real; clinical significance tells us if the results are important for practice” (Houser, 2018, p. 356). Both statistical significance and clinical significance relate to quantitative data.

Statistical significance could mean that in 0.5% of the population x, y, and z occurred. The probability of it happening could be chance because it is such a small percentage of the population. Clinical significance shows to what degree the new intervention is needed to make a difference in a client’s life. Clinical significance is thought to be much more meaningful but without the initial statistical significance, further studies would not have been done to prove a clinical significance. In reference to practice, clinical significance is more important when applying evidence to my practice. When utilizing clinical significance, there is evidence-based support of your actions.

“The goal of statistical inference is to estimate likely true or large-sample effects based on random samples from the collective(s) of interest” (Wilkinson & Winter, 2014, p. 492). In a study, the variances between groups are measured quantitatively and examined using inferential statistics. Inferential statistics utilize numbers to determine the probability that random error plays a role in the outcome. It also suggests that independent variables have an effect on the results. Descriptive statistics are usually related to the mean, minimum, maximum, standard deviation, and median of results. These studies are not usually utilized for change in evidence-based practice but are more likely to be used to measure current practice.

An example of inferential statistics would be if I questioned all of the Emergency Department nurses at my facility about the effects of education on compassion fatigue. The results would infer that the results would be the same in another location but I only used a small population. For the descriptive statistics, I would use a table, graph, or chart in addition to the statistical data to summarize my study.

~Candee Crane

References

• Houser, J. (2018). Nursing research Reading, using, and creating evidence (4th ed.). Sudbury, MA Jones & Bartlett.
• Wilkinson, M., & Winter, E.M. (2014). Clinical and practical importance vs statistical significance Limitations of conventional statistical inference. International Journal of Therapy & Rehabilitation, 21(10), 488-495.