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A test for homogeneity of variance was also presented in the output. Levene’s test was applied to measure the homogeneity of the variance. From the table, it can be observed that the p-value which resulted from Levene’s tests was 0.122. The implication is that the difference was not significant since the value is above the threshold value, which is usually considered 0.05 (Aslam, 2020).
The next test provided in the output is ANOVA. The ANOVA tests represent the interaction within the group and between the groups of “overall satisfaction” and “material well-being.” One of the interpretations that can be drawn from the ANOVA output is that there was a statistically significant difference between the groups. The analysis indicate that the p-value is 0.000, which is well below the threshold of 0.05, hence a statistical significance (Stoker et al.,2020). The value means that the mean of overall satisfaction and material well-being is statistically significant. This test is limited in that it can not be used to explore how the groups are different from each other; therefore, a multiple-comparison computation can be carried out using the Tukey post hoc test.
Another relevant analysis is multiple comparisons of “overall satisfaction” and “material well-being.” This analysis was performed at 0.05 level of confidence. The results obtained indicate a statistically significant difference between the means of the tested groups. It was highlighted in the previous paragraph that the Tukey post hoc test can be used for a more extensive study and exploration of the variables (Nanda et al.,2021). The test has been used to carry out post hoc tests on one-way ANOVA tests. As such, the output also shows the Tukey post hoc test as part of the ANOVA. The use of ANOVA in testing for the similarity of three or more group means, the obtained findings would show that all the group means are not similar.
It is also worth noting that the ANOVA output has not identified if there are any significant differences between the mean pairs. Therefore, post hoc tests is used to determine the differences between the means of the groups while also ensuring that the standard errors are controlled (Grey & Grove, 2020). From the analysis, it is evident that the difference in overall satisfaction between no housing problems and one housing problem was 0.739, which can be considered significant. The next part is the difference in the overall satisfaction between no housing problems and two or more housing problems, a value which was observed to be 2.139, which is also significant. The next data shows the " name="description">
Data collection and analysis play a significant role in enabling researchers in different fields to make informed decisions as appropriate. Therefore, researchers employ statistical analysis to convert the data into valuable information that they can interpret and use to make informed decisions. It is vital for nurses, just like researchers in other fields, to be in a position to perform statistical analysis and subsequent analysis for decision-making and improvement of patient care and outcomes (Grey & Grove, 2020). The implication is that nurses should possess adequate knowledge that enables them to determine which statistical tests to use in specific cases. T-tests and Analysis of Variance (ANOVA) have been used in research for a long time. While ANOVA can be used to compare data between two or more groups or conditions under investigation to determine if there is a difference, the T-test is used for two groups (Connelly, 2021). As such the purpose of this assignment is to provide a summary of the interpretation of ANOVA offered in the output.
The output data is on material well-being and overall satisfaction, with the data covering comparisons, ANOVA, tests for Homogeneity of variance, and descriptive statistics. In the interpretation of the output, the first part to start with is the descriptive table. This table presents the standard deviation, mean, and 95% confidence interval for the dependent variables for every group in the study. The mean for “No housing problem” is 12.71, “One housing problem” is 11.93, while the mean for “two or more housing problems” is 10.57. the corresponding standard deviations for the three categories are 2.353, 2.588, and 2.594. From the table, it can also be observed that the overall mean for “No housing problem,” “One housing problem,” and “two or more housing problems” is 11.80
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A test for homogeneity of variance was also presented in the output. Levene’s test was applied to measure the homogeneity of the variance. From the table, it can be observed that the p-value which resulted from Levene’s tests was 0.122. The implication is that the difference was not significant since the value is above the threshold value, which is usually considered 0.05 (Aslam, 2020).
The next test provided in the output is ANOVA. The ANOVA tests represent the interaction within the group and between the groups of “overall satisfaction” and “material well-being.” One of the interpretations that can be drawn from the ANOVA output is that there was a statistically significant difference between the groups. The analysis indicate that the p-value is 0.000, which is well below the threshold of 0.05, hence a statistical significance (Stoker et al.,2020). The value means that the mean of overall satisfaction and material well-being is statistically significant. This test is limited in that it can not be used to explore how the groups are different from each other; therefore, a multiple-comparison computation can be carried out using the Tukey post hoc test.
Another relevant analysis is multiple comparisons of “overall satisfaction” and “material well-being.” This analysis was performed at 0.05 level of confidence. The results obtained indicate a statistically significant difference between the means of the tested groups. It was highlighted in the previous paragraph that the Tukey post hoc test can be used for a more extensive study and exploration of the variables (Nanda et al.,2021). The test has been used to carry out post hoc tests on one-way ANOVA tests. As such, the output also shows the Tukey post hoc test as part of the ANOVA. The use of ANOVA in testing for the similarity of three or more group means, the obtained findings would show that all the group means are not similar.
It is also worth noting that the ANOVA output has not identified if there are any significant differences between the mean pairs. Therefore, post hoc tests is used to determine the differences between the means of the groups while also ensuring that the standard errors are controlled (Grey & Grove, 2020). From the analysis, it is evident that the difference in overall satisfaction between no housing problems and one housing problem was 0.739, which can be considered significant. The next part is the difference in the overall satisfaction between no housing problems and two or more housing problems, a value which was observed to be 2.139, which is also significant. The next data shows the difference between one housing problem a
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