Statistics in nursing | Nursing homework help

Types of Statistical Tests: Parametric tests are used when the data is normally distributed and the sample size is large. These tests assume that the data is interval or ratio level, meaning that the measurements are continuous and have a fixed scale. Examples of parametric tests include paired and independent samples t-tests, ANOVA, and linear regression.

Non-parametric tests, on the other hand, are used when the data is not normally distributed or the sample size is small. These tests do not assume that the data follows a particular distribution, and they can be used for ordinal or nominal data. Examples of non-parametric tests include Mann Whitney U, Wilcoxon signed-rank test, and Kruskal-Wallis H test.

Report of Test Results: When reporting the test results, it is important to state the alpha level used for the significance criterion for all tests in the project at the beginning of the data analysis and results section. For example, “An alpha or significance level of < .05 was used for all statistical tests in the project.”

If the p-value is less than the alpha level, the result is considered statistically significant. For example, “A statistically significant difference was noted between the scores before compared to after the intervention t(24) = 2.37, p = .007.”

If the p-value is greater than the alpha level but in the predicted direction, it is considered marginally significant. For example, “Scores indicated a marginally significant preference for the intervention group (M = 3.54, SD = 1.20) compared to the baseline (M = 3.10, SD = .90), t(24) = 1.37, p = .07.”

If the p-value is over .10, the results are considered non-significant, but if there is a trend in the predicted direction, it should be reported. For example, “Results indicated a non-significant trend for the intervention group (14) over…”

Appendix: A comparison table of the variable’s level of measurement is provided as an appendix to the paper. This table displays the dependent variables and their level of measurement, whether nominal, ordinal, interval, or ratio.

Moreover, the outputs from the statistical analysis are also provided in the appendix to the paper. For instance, the means, standard deviations, t-statistic, degrees of freedom, p level, and chi-square statistic are reported for each test.