NR716 Week 5 Discussion Analyzing Descriptive Statistics
Purpose
The purpose of this discussion is for you to demonstrate an understanding of the DNP-prepared nurse’s role in the work of both appraising statistical tests in quantitative research studies and the application of descriptive statistical tests to a practice change project.
Instructions
Consider the following scenario:
As a DNP-prepared nurse working in a rural clinic, you have a large population of patients with type 2 diabetes whose weight exceeds a healthy body mass index (BMI) and are overweight or obese. You design an 8-10 week DNP practice change project to impact weight.
Based on an exhaustive search and appraisal of research studies, you select a statistically significant evidence-based intervention—an exercise program- to translate to your local rural clinic.
Before implementing the intervention, you retrieve aggregate data of weights for all participating patients.
You collect the same data, the patient weights, after implementation of the evidence-based intervention of the exercise program to your patients.
Pre-implementation and post-implementation data include the following.
| Patient | Pre-Intervention Weight | Post Intervention Weight |
| 1 | 225 | 218 |
| 2 | 196 | 190 |
| 3 | 190 | 188 |
| 4 | 229 | 225 |
| 5 | 292 | 288 |
| 6 | 188 | 178 |
| 7 | 188 | 190 |
| 8 | 201 | 190 |
| 9 | 179 | 172 |
| 10 | 191 | 186 |
As a DNP-prepared nurse, you will analyze descriptive statistics, such as measures of central tendency and variability, to describe outcomes of a practice change project. Reflect upon this scenario and the data presented.
What conclusions would you make at the end of this practice change project? What recommendations would you make to stakeholders for continuing the exercise program based on these results?
In order to respond to this discussion question, you will first need to complete the following calculations and consider responses to your analysis of the descriptive statistics.
- Perform the following calculations:
- Based on the data set provided, calculate the mean pre-implementation and post-implementation weight values for patients involved in this practice change project.
- Now calculate the pre-implementation and post-implementation median weight of the patients.
- Next, calculate the pre-implementation and post-implementation modes.
- Finally, calculate the pre-implementation and post-implementation range of patient weights. If no outliers exist, the range will determine how close the weights are to the patients involved.
- Based on your analysis of the descriptive statistics, what determinations related to the mean weights following implementation of the evidence-based intervention can be made?
- As you reflect upon the weights of the patients, you observe that patient #5 has weights that are outliers. What does this do to your understanding of the data?
Solution:NR716 Week 5 Discussion Analyzing Descriptive Statistics
- Calculations
- Mean (Average) Weight:
Pre-Implementation: 207.9 lbs.
Post-Implementation: 202.5 lbs.
- Median Weight:
Pre-Implementation: 193.5 lbs.
Post-Implementation: 190.0 lbs.
- Mode (Most Frequent Weight):
Pre-Implementation: 188 lbs.
Post-Implementation: 190 lbs.
- Range (Difference between Maximum and Minimum Weights):
Pre-Implementation: 113 lbs. (292 – 179)
Post-Implementation: 116 lbs. (288 – 172)
- Determinations
The mean and median weight both decreased post-implementation by respectively 5.4 lbs. and 3.5 lbs., indicating that the evidence-based exercise program was effective in promoting weight loss among the participants. While the reduction is modest, it indicates progress in weight management, which could be more significant over an extended period. However, some patients……Click on the PayPal icon below to purchase full solution for $5
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