NR 439 Week 6: Data Results and Analysis Discussion
NR 439 Week 6: Data Results and Analysis
NR 439 Week 6: Data Results and Analysis Discussion – Class this week we are going to review the data collected. Our discussion will review the following course outcomes.
CO2: Apply research principles to the interpretation of the content of published research studies. (PO: 4, 8)
CO4: Evaluate published nursing research for credibility and clinical significance related to evidence-based practice. (PO: 4, 8)
After the data are collected, it is time to analyze the results!
After the data are collected, it is time to analyze the results!
- Discuss one of the four basic rules for understanding results in a research study.
- Compare clinical significance and statistical significance. Which one is more meaningful when considering applying evidence to your practice?
- Compare descriptive statistics and inferential statistics in research. Please give an example of each type that could be collected in a study that would be done on your nursing clinical issue you identified in previous weeks.
Discuss one of the four basic rules for understanding results in a research study.
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NR 439 Week 6: Data Results and Analysis Discussion
According to CCN, 2017-week 6 lesson, the four basic rules for understanding results in a research study are: Understanding 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. My discussion will be focused on rule # 2 Identify the variables-dependent and independent. Business dictionary defines variable as a characteristic, number, or quantity that increases or decreases over time, or takes different values in different situations. There are two basic types of variables (1) Independent variable that can take different values and can cause corresponding changes in other variables, and (2) Dependent variable are those that can take different values only in response to an independent variable (businessdictionary.com). An example of a variable is patient’s vital signs. We can measure a patient’s vital signs, but they can increase or decrease.
Compare clinical significance and statistical significance. Which one is more meaningful when considering applying evidence to your practice?
Clinical significance is generally expected to reflect the extent to which an intervention can make a real difference in patients’ lives. Statistical significance is the comparison of differences to standard error and the calculation of the probability of error that gives inferential analysis its strength. Nevertheless, statistical significance is just one of the important measures that determine whether research is truly applicable to practice (Houser, 2018). Statistical significance is a requirement for using evidence in practice: If results are due to error, then their application is irrelevant. At the same time, statistical significance tells the nurse little about whether the results will have a real impact in patient care. (Houser, 2018).
Compare descriptive statistics and inferential statistics in research. Please give an example of each type that could be collected in a study that would be done on your nursing clinical issue you identified in previous week.
Descriptive statistics use numbers narratively, in tables, or in graphic displays to organize and describe the characteristics of a sample (Houser, 2018, p291). It uses data to provide descriptions of the population, either through numerical calculations or graphs or tables. Descriptive statistics are the characteristics that are given to the sample of a research study. Descriptive statistics tell us, who was in the study and what did the study show us about the hypothesis (CCN, 2018). An example of descriptive statistics is my research question: Will follow-up telephone call and visit by home health nurse 3 to 7 days post discharge help reduce the rate of hospital readmission for patients 65 years and above with CHF. The descriptive study for my research will be patients 65 years old and above with CHF.
Inferential statistics can help to make a general statement about the sample population and compare them with other populations. (Houser, 2018). It makes inferences and predictions about a population based on a sample of data taken from the population in question. Inferential statistics help answer the question. How strong is the evidence from the study? “An example of inferential statistics will be all patients 65 years and above with CHF will not experience hospital readmission if they receive follow-up telephone calls and visit by home health nurse 3 to 7 days post discharge.
NR 439 Week 6: Data Results and Analysis Discussion References
Houser, J. (2018). Nursing research: Reading, using, and creating evidence (4th ed.). Sudbury, MA: Jones & Bartlett.
http://www.businessdictionary.com/definition/variable.html
https://chamberlain.instructure.com/courses/7426/pages/week-6-lesson?module_item_id=567652