Student’s t test and Nonparametric Statistics OT 667 Hypothesis testing defined A method for deciding if an observed effect or result occurs by chance alone OR if we can argue the results actually happened as a result of an intervention. The Null Hypothesis
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
A method for deciding if an observed effect or result occurs by chance alone
if we can argue the results actually happened as a result of an intervention.
In order to decide if the results of an experiment occur by chance or if the effects seen are the result of a treatment, researchers declare a null hypothesis (Ho) and an alternative or research hypothesis (Ha).
To test a hypothesis, researchers talk about “rejecting the null” in order to demonstrate the treatment has an effectOR“accepting the null” if the treatment does not have an effect.
When you reject the null, you say that there IS a significant difference between the groups, indicating the likelihood the treatment was effective.
Interval and ratio
The difference between the group means divided by the difference between the variability within the groups
The variance gives you the degree of variability within each group
Between group differences there is no difference (which is the null hypothesis) is correct. and within group differences are important factors to remember - they are used to calculate ANOVA as well as t tests.
mean of the difference scores___
standard error of the difference scores
The number that results from a t test is called the “ there is no difference (which is the null hypothesis) is correct.calculated value” of the test. This number is then compared in a table to the “critical value” using the alpha level set for the study.
Independent samples t test when variances between groups are equal and when they are unequal
Paired t tests
One way ANOVA
Mann-Whitney U test
Wilcoxon Signed-Ranks Test
Kruskal-Wallis one way analysis of variance by ranks
Friedman Two WayComparable Parametric and Nonparametric Tests
Remember Venn diagrams and relationships? procedure as with parametric tests.