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Step 1: Testing Method. Step 2: Assumptions. Step 3: Hypotheses. Step 4: Calculate the test statistic. Step 5: Determine p-value and compare with the significance level.
Set up hypotheses and select the level of significance. Select the appropriate test statistic. Set up decision rule. Compute the test statistic. Conclusion. Set up hypotheses and determine level of significance. Select the appropriate test statistic.
Mood's Median: compares the medians of two or more population samples. Welch's T-test: tests for equality of means between two population samples. Also known as Welch's unequal variances t-test. Kruskal-Wallis H Test: compares two or more groups with an independent variable, based on a dependent variable.
Three criteria are decisive for the selection of the statistical test, which are as follows: the number of variables, types of data/level of measurement (continuous, binary, categorical) and. The type of study design (paired or unpaired).
A one-way analysis of variance (ANOVA) is used when you have a categorical independent variable (with two or more categories) and a normally distributed interval dependent variable, and you wish to test for differences in the means of the dependent variable broken down by the levels of the independent variable.
The two main types of statistical analysis and methodologies are descriptive and inferential. However, there are other types that also deal with many aspects of data including data collection, prediction, and planning.
The chosen statistical tests are the chi- square test, chi-square test for goodness of fit, chi-square test for independence, Fisher's exact test, McNamara's test and the use of confidence intervals for proportions.
1:43 11:09 Suggested clip How to calculate t statistics test between the means of related YouTubeStart of suggested client of suggested clip How to calculate t statistics test between the means of related
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