DNP 830 Working With Inferential Statistics
University:
GCU
DNP 830 Working With Inferential Statistics
Paper Instructions
Assessment Description
This topic helps you develop a basic understanding of statistics. Two distinct types of statistics are addressed descriptive and inferential. In this assignment, you will have another opportunity to use the SPSS program. SPSS makes it easy to analyze data using specific tests. This assignment will give you practice with t-tests, ANOVA, and communicating your results through a written summary.
General Requirements
Use the following information to ensure successful completion of the assignment
Before beginning this assignment, be sure to view the tutorial videos located in the topic Resources.
View the “Working With Inferential Statistics” tutorial, located in the DNP-830A folder of the DNP PI Workspace.
Refer to the “Sample Analysis of Variance (ANOVA) Table” and “Sample Results of Several t Tests Table” in the topic Resources, as needed, to complete the table using APA style.
Doctoral learners are required to use APA style for their writing assignments. The APA Style Guide is located in the Student Success Center.
This assignment uses a rubric. Review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.
You are not required to submit this assignment to LopesWrite.
Learners will submit this assignment using the assignment dropbox in the digital classroom. In addition, learners must upload this deliverable to the Learner Dissertation Page (LDP) in the DNP PI Workspace for later use.
Directions
Prior to beginning this assignment, complete the assigned readings and view the assigned videos. Using the data provided on the “HCUP State Inpatient Databases (SID) File Composition – Number of Discharges by Year” webpage, located in the topic Resources, conduct the appropriate statistical test in SPSS to address the following
Describe the mean, standard deviation, and range of discharges in 2019.
Compare the number of discharges in 2019 in all states by region using an ANOVA. Are there significantly more discharges? Describe the assumption of variance between groups and within groups?
Create a table of your results using APA style and attach as an appendix to your paper. Western States (Washington, Oregon, Idaho, Montana, Wyoming, California, Nevada, Utah, Arizona, New Mexico, Colorado Alaska, Hawaii); Mid-Western States (North Dakota, South Dakota, Nebraska, Kansas, Minnesota, Iowa, Missouri, Wisconsin, Illinois, Indiana, Michigan, Ohio); Southern States (Maryland, Washington D.C, West Virginia, Virginia, Kentucky, North Carolina, South Carolina, Georgia, Florida, Tennessee, Alabama, Mississippi, Arkansas, Louisiana, Oklahoma, Texas); Northeastern States (Maine, Vermont, New Hampshire, Massachusetts, Rhode Island, Connecticut, New York, New Jersey, Pennsylvania, Delaware).
Compare the number of discharges in all states between 2012 and 2019 using a paired t-test. Are there significantly more discharges in 2019 versus 2012? Describe the assumption of a paired samples t-test. Create a table for your results using APA style and attach as an appendix.
Write a 500–750-word summary of your results.
Attach your SPSS statistical outputs as an appendix to your paper.
Portfolio Practice Immersion Hours
It may be possible to earn portfolio practice immersion hours for this assignment. Enter the following after the References section of your paper
Practice Immersion Hours Completion Statement DNP-830A
I, (INSERT NAME), verify that I have completed and logged (NUMBER OF) clock minutes/hours in association with the goals and objectives for this assignment. I also have tracked said practice immersion hours in the Lopes Activity Tracker for verification purposes and will be sure that all approvals are in place from my faculty and practice immersion preceptor/mentor before the end of the course.
Resources
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Clinical Analytics and Data Management for the DNP
Read Chapters 2 and 14 in Clinical Analytics and Data Management for the DNP.
View Resource
Statistical Significance or Clinical Significance? A Researcher’s Dilemma for Appropriate Interpretation of Research Results
Read
Sharma, H. (2021). Statistical significance or clinical significance? A researcher’s dilemma for appropriate interpretation o
… Read More
- https //lopes.idm.oclc.org/login?url=https //search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=152241211&site=ehost-live&scope=site&custid=s8333196&groupid=main&profile=ehost
HCUP State Inpatient Databases (SID) File Composition – Number of Discharges by Year
Review the data on the HCUP webpage to complete the topic assignment
Healthcare Cost and Utilization Project. (2021). HCUP sta
… Read More
- https //hcup-us.ahrq.gov/db/state/siddist/siddist_discharge.jsp
Use Landscape and Portrait Orientation and Use Both in the Same Document
Review the following video resources, located on the Microsoft Support website, for assistance in attaching tables or charts in landscape
… Read More
- https //support.microsoft.com/en-us/office/video-use-landscape-and-portrait-in-the-same-document-ddd80cb6-c9ae-4493-ba75-c663074031a0
Sample Analysis of Variance (ANOVA) Table
Refer to “Sample Analysis of Variance (ANOVA) Table,” in the following APA Style resource, for assistance with APA style formatti
… Read More
- https //apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables#anova
Sample Results of Several t Tests Table
Refer to “Sample Results of Several t Tests Table,” in the following APA Style resource, for assistance with APA style f
… Read More
- https //apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables#tests
Sample Size
Read
Grand Canyon University, Center for Innovation in Research and Teaching. (n.d.). Sample size.
- https //cirt.gcu.edu/research/developmentresources/realworld/samplesize
Calculating Sample Size A Quick Guide (Calculator Included)
Read
Qualtrics. (2020, May 21). Calculating sample size A quick guide (calculator included).
- https //www.qualtrics.com/blog/calculating-sample-size/
Working With Inferential Statistics
View the “Working With Inferential Statistics” tutorial, located in the DNP-830A folder of the DNP PI Workspace for assistance in
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Sample Answer
Working with Inferential Statistics
Analysis of collected data is key in determining the impacts of an intervention in a project. One of the approaches used is inferential statistics. In inferential statistics, various analytical tools are used to help draw conclusions by examining random samples in a population.
The analysis also offers further and finer details about the sampled data, such as the relationship between variables that exist in a dataset (Oh &Pyrczak, 2023). Therefore, inferential statistics help in making generalizations regarding a population by using various approaches, such as t-tests and analysis of variance (ANOVA), among other statistical approaches.
As such, the purpose of this assignment is to use the SPSS program to analyze specific tests for a given data set and communicate the results.
Mean, Standard Deviation, and Range
The data on the number of discharges by year was analyzed. The mean of the discharges in 2019 is 720,811.89. This analysis shows an increase in the number of discharges as compared to 2017 and 2018.
The analysis also showed that the standard deviation from the calculated mean is 823,479.26. The standard deviation value is not deviating a lot from the population (Mishra et al., 2019). The implication is that the recorded discharges from the states do not vary by wider margins. The analysis also shows that the range of the discharge summaries recorded in the same year is 3,770,020.
ANOVA
The number of discharges recorded in the year 2019 is of significance since it shows that each state had increased cases of discharge. It was also important to include data from the previous years and the years after to show trends in the number of discharges and enable comparisons. For example, it is conceivable that there was a further variance in 2020.
The enhanced rates of discharge are a reflection of measures put in place in the previous year to help affect the rates of discharge. As shown in the appendix, the variance between groups and within groups of the other years with the data collected in 2019 is significant.
The western and mid-western states have a small variance, while southern and northeastern states have a fairly large variance. However, the variance recorded in all these groups is significant because the p<0,000, which is significant for all the states (Amrhein et al., 2019).
T-Test
Another analysis performed is the t-test. The paired sampled t-test shows a bivariate Pearson correlation coefficient that gives hypothesized results. The paired samples between 2012 and 2019 have a t= 0.493. The implication is that there are significantly more discharges in 2019 as compared to 2012.
The paired sampled t-test assumes that the mean of the patients discharged in 2012 and 2019 are not the same (Stapor, 2020). Therefore, the mean of patients discharged in 2012 is low, while the mean of those discharged in 2019 is high.
As such, the analysis is an indication that there was an increase in the number of patients discharged in the year 2019 as compared to 2012. Another insight that can be obtained from the analysis is that while the number of discharges recorded in the year 2012 was significantly lower, this value steadily increased as the year progressed.
Conclusion
The analysis has been performed on the discharge summaries of the provided data. T-tests and ANOVA have both been performed on the data to help generalize the discharge summaries recorded for the year 2019. In addition, it was also noted that the number of discharges recorded in 2019 was significantly higher as compared to those in 2012. The number of discharges also steadily increased from 2012.
References
Amrhein, V., Trafimow, D., & Greenland, S. (2019). Inferential statistics as descriptive statistics There is no replication crisis if we don’t expect replication. The American Statistician, 73(sup1), 262-270. https //doi.org/10.1080/00031305.2018.1543137
Mishra, P., Pandey, C. M., Singh, U., Gupta, A., Sahu, C., & Keshri, A. (2019). Descriptive statistics and normality tests for statistical data. Annals of Cardiac Anaesthesia, 22(1), 67. https //doi.org/10.4103%2Faca.ACA_157_18
Oh, D. M., & Pyrczak, F. (2023). Making sense of statistics A conceptual overview.
Stapor, K. (2020). Descriptive and inferential statistics. In Introduction to Probabilistic and Statistical Methods with Examples in R (pp. 63-131). Springer, Cham. DOI 10.1007/978-3-030-45799-0_2
Appendices
Statistics
2019
N Valid 33
Missing 3
Mean 720811.8485
Median 473313.0000
Mode 57180.00a
Std. Deviation 823479.25580
Range 3770020.00
Minimum 57180.00
Maximum 3827200.00
a. Multiple modes exist. The smallest value is shown
ANOVA
Sum of Squares df Mean Square F Sig.
2012 Between Groups 10622628681292.960 25 424905147251.718 . .
Within Groups .000 0 .
Total 10622628681292.960 25
2013 Between Groups 10365010799004.518 26 398654261500.174 . .
Within Groups .000 0 .
Total 10365010799004.518 26
2014 Between Groups 10645313957132.678 27 394270887301.210 . .
Within Groups .000 0 .
Total 10645313957132.678 27
2015 Between Groups 11219616544191.310 28 400700590863.975 . .
Within Groups .000 0 .
Total 11219616544191.310 28
2016 Between Groups 11570788618594.668 29 398992710986.023 . .
Within Groups .000 0 .
Total 11570788618594.668 29
2017 Between Groups 11699386760499.500 31 377399572919.339 . .
Within Groups .000 0 .
Total 11699386760499.500 31
2018 Between Groups 21562390146133.336 32 673824692066.667 . .
Within Groups .000 0 .
Total 21562390146133.336 32
2020 Between Groups 15100282452033.887 25 604011298081.356 . .
Within Groups .000 0 .
Total 15100282452033.887 25
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 2012 686773.0385 26 651847.48772 127837.80999
2019 679626.0000 26 654549.84684 128367.78622
Paired Samples Correlations
N Correlation Significance
One-Sided p Two-Sided p
Pair 1 2012 & 2019 26 .994 <.001 <.001
Paired Samples Test
Paired Differences t df Significance
Mean Std. Deviation Std. Error Mean 95% Confidence Interval of the Difference One-Sided p Two-Sided p
Lower Upper
Pair 1 2012 – 2019 7147.03846 73894.48405 14491.90062 -22699.58957 36993.66649 .493 25 .313 .626
Paired Samples Effect Sizes
Standardizera Point Estimate 95% Confidence Interval
Lower Upper
Pair 1 2012 – 2019 Cohen’s d 73894.48405 .097 -.290 .481
Hedges’ correction 76207.72538 .094 -.281 .466
a. The denominator used in estimating the effect sizes.
Cohen’s d uses the sample standard deviation of the mean difference.
Hedges’ correction uses the sample standard deviation of the mean difference plus a correction factor.
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