Week 8 Discussion

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South University, Savannah *

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NSG6101

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Statistics

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Feb 20, 2024

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Uploaded by DoctorSheepMaster1015

Non-parametric and parametric tests are two methods of statistical analysis to determine the rationality of a given hypothesis. Parametric tests are calculated by statistical distributions in data while non-parametric do not rely on any distribution. Furthermore, non-parametric testing does not make any inference, but measures the central tendency with the median value (Difference between parametric and nonparametric test, 2020). One example of a non-parametric testing is the Kruskal-Wallis Test. This serves as a method for testing whether samples are originated from the same distribution. Kruskal-Wallis tests are typically used when researchers are studying three or more categorical, independent groups (e.g., three ethnic groups: Caucasian, African American and Hispanic). Four assumptions must be met by the investigator to run this test. They are as follows: 1. Your dependent variable should be measured at the ordinal or continuous level (i.e., interval or ratio). 2. Your independent variable should consist of two or more categorical , independent groups. 3. You should have independence of observations, (i.e., no relationship between the observations in each group or between the groups themselves). 4. Interpretation of a Kruskal-Wallis test relies on determining whether the distributions in each group have the same shape (i.e., the same variability). (Kruskal-Wallis H Test using SPSS Statistics, 2018, para 7) An example of a parametric test is the One-Way ANOVA (“analysis of variance”). This test compares the means of two or more independent groups in order to discover whether there is statistical evidence to prove that the corresponding population means are significantly different (One-Way ANOVA, 2022). This test is frequently used in field studies, experiments, and quasi- experiments. There are three primary assumptions required for a One-Way ANOVA. They are as follows: 1. Every sample must be randomly selected from a normal distribution. 2. These distributions have the same variance. 3. All samples must be independent of each other. (One-Way ANOVA, 2022, para 3) References: Difference between parametric and nonparametric test. (2020, December 17). BYJU’s. https://byjus.com/maths/difference-between-parametric-and- nonparametric/#:~:text=The%20key%20difference%20between%20parametric,ten dency%20with%20the%20median%20value Kruskal-Wallis H Test using SPSS Statistics. (2018). Laerd Statistics. https://statistics.laerd.com/spss-tutorials/kruskal-wallis-h-test-using-spss- statistics.php#:~:text=Typically%2C%20a%20Kruskal%2DWallis%20H,commonl y%20used%20for%20two%20groups One-Way ANOVA. (2022, November 3). Kent State University. https://libguides.library.kent.edu/SPSS

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