1) Write a paper of 1,000-1,250 words regarding the statistical significance of outcomes as presented in Messina's, et al. article “The Relationship between Patient Satisfaction and Inpatient Admissions Across Teaching and Nonteaching Hospitals.”

2) Assess the appropriateness of the statistics used by referring to the chart presented in the Module 4 lecture and the resource “Statistical Assessment.”

3) Discuss the value of statistical significance vs. pragmatic usefulness.

4) Prepare this assignment according to the APA guidelines found in the APA Style Guide located in the Student Success Center. An abstract is not required.

5) This assignment uses a grading rubric. Instructors will be using the rubric to grade the assignment; therefore, students should review the rubric prior to beginning the assignment to become familiar with the assignment criteria and expectations for successful completion of the assignment.

 

HLT540.v10R.StatisticalAssessment_student.docx

Statistical Assessment

 

Use the chart in the Module 4 lecture to complete the table below to assess the appropriateness of the statistics used, and determine the statistical significance of outcomes in Messina’s, et al., article “The Relationship Between Patient Satisfaction and Inpatient Admissions Across Teaching and Nonteaching Hospitals” . Refer specifically to the discussion on pages 189-90 of the article.

Messina, D., Scotti, D., Ganey, R., Zipp, G., & Mathis, L. (2009). The Relationship Between Patient Satisfaction and Inpatient Admissions Across Teaching and Nonteaching Hospitals. Journal of Healthcare Management, 54(3), 177-89, discussion 189-90. Retrieved from http://library.gcu.edu:2048/login?url=http://proquest.umi.com.library.gcu.edu:2048/pqdweb?did=1752526601&sid=1&Fmt=4&clientId=48377&RQT=309&VName=PQD

 

 

Statistic	Data type	Sample Size	Research Question

 

 

 

Statistical Significance:

 

 

 

 

 

 

 

 

 

There were three errors in Table 4 on page 185. In your identification of significant findings, can/did you find them?

 

The chart from the Module 4 Readings:

Statistic	Data Type	Sample Size	Research Question
Mean and Standard Deviation	Interval or ratio	>2	What does the data set look like?
Frequency Distribution	Nominal-Ratio	>2	What does the data set look like?
Chi-Square	Nominal-Ordinal	>4	Is the variance of one variable equal to or different from another variable
Correlation Coefficient	Interval-Ratio	>4	What is the relationship between two variables?
t-Test	Interval-Ratio	<30	Is there a significant difference between two groups? May be intrinsic or may be experimental
ANOVA (Analysis of Variance)	Interval-Ratio	>30	Is there a significant difference between 2 or more groups?
Regression Analysis	Interval-Ratio	>30	How much of the change in the dependent variable is predicted by the independent variable or variables?

 

 

Refer to the Module 4 Readings for explanation of the chart.

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This is a response to someone else’s post, need one reference, no min word count.

Partial correlation is the relationship between two variables while controlling for a third variable. It can also be viewed as a three way overlap (a-b-c) and then remove c in the picture in order to determine the correlation between any two of the variables (a &b) especially if c is constant. If c is not constant, then there is certain amount of correlation found any of the variables is tied in with the correlation that each of those two (a & b) has with c.

My example: “a” is the amount of effort spent on making the discussion in an on-line education by the graduate student in nursing, “b” is the graduate student’s score on the discussion in online education, “c” is a measure of time where the graduate student work as a nurse in any institution while taking an online class.

Independent variable is seen as having an effect on the dependent variable (Kellar & Kelvin, 2013). In the sample, “a” (which is the amount of effort spent on making the discussion in an online education by the graduate student in nursing) is the independent variable while “b”(score of the graduate student in an online education) is the dependent variable which is referred to as outcome variable or the response variable. “c” (measure of time when the graduate student work as nurse in any institution while taking an online class) is the confounding variable, which is defined as other than the independent variable that may affect the dependent variable (Mc Donald, 2014).

Partial correlation is the most appropriate test on the sample given because there is a 3rd variable that might mislead or distract the result of comparison of first and second variable. Partial correlation is a technique that allows to describe the relationship between the two variable after statistically controlling the 3rd variable (Kellar & Kelvin, 2013). Thus in my sample study, to be able to obtain the right relationship between “a” and “b” is to make “c” constant. I would control my “c” as selecting my subjects as only graduate students in nursing, who are taking an online education while working as a full-time nurse in any institution. Therefore, if the 3rd variable is controlled statistically, then the outcome will attain a true result.

References:

Kellar, S. & Kelvin, E. (2013). Munro’s statistical methods for health care research (6th ed.). Philadelphia; Wolters Kluwer/ Lippincot.

 

Mc Donald, M. (2014). Handbook of biological statistics (3rd ed.). Maryland: Sparky House Publishing.