This doctoral-level assessment demonstrates the application of t-tests and ANOVA statistical methods in healthcare research, specifically analyzing patient satisfaction and wait times across affiliated practices. The study examines 50 patients across three groups with different housing problem levels, revealing significant mean differences in overall satisfaction. The analysis includes comprehensive descriptive statistics, Levene's test for variance equality, and post-hoc comparisons to identify specific group differences.
The current paper aims to apply a statistical analysis technique through the t-test and ANOVA test, which aid in making inferences about the sample parameter. In basic terms, inferential statistics aim to infer the population using the sample drawn (Connelly, 2021). Therefore, as a DNP-prepared nurse, my task is to evaluate the patient’s care and make a comparison to the patient’s care at affiliated practices. There have been key complaints from the patients concerning the wait times associated with each patient visit. Thus, I decided to compare the wait times at affiliated practices. A sample of 50 individual patients was collected and analyzed using t-test and ANOVA, which aim at comparing the data between two or more groups or some conditions understudy to investigate if there exists some differences/disparities between those groups under investigation on some continuous dependent variable (Gray & Grove, 2020). Thus, the ANOVA test will investigate the differences in the means of the overall satisfaction among the three groups.
My study aimed to describe and summarize the data provided using descriptive statistics to summarize the data more successfully without making inferences. From the results obtained above, the study aimed to assess the differences in the overall satisfaction among the three groups (no housing, one housing, and two or more housing problems). The descriptive results show that the no housing problem had a mean and standard deviation (M=12.71, SD=2.35), one housing problem(M=11.97, SD=2.59), and two or more housing (M=10.57, SD=2.59). The results indicate that the no housing problem had a higher mean than other housing problems.
Before conducting the statistical analysis, it is imperative to assess the assumptions of the ANOVA test through the use of Levene’s test (Nick, 2007). From Levene’s test results, the equality of variance has been assumed, indicating that variance across the three groups is the same (p>0.05).
From the ANOVA results obtained, we can say that there was a significant mean difference between the overall satisfaction among the three groups, no, one, and two or more housing problems (F (2,934) =61.67, pFrom the results obtained in the ANOVA results, since we had a statistical mean difference of the overall satisfaction among the three groups, a post-hoc test was conducted to know which of the specific group differed. We can see from the table in the multiple comparisons that there is a substantial/significant difference in overall satisfaction between the no housing problem and one housing problem (pConclusion
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