Outline, define, and explain the assumptions for the three major analyses discussed in this unit: the...

Outline, define, and explain the assumptions for the three major analyses discussed in this unit: the independent-groups t-test, the correlated-groups t-test, and the one-way between-subjects ANOVA. Why are these assumptions important? How are these assumptions assessed/tested by statisticians? What do they have to do with the robustness of a statistical test? Explain and be specific, and treat this question as an essay (i.e., write in complete sentences and be thorough)!

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Expert Solution

Assumptions

One-Way ANOVA

Normality – That each sample is taken from a normally distributed population
Sample independence – that each sample has been drawn independently of the other samples
Variance Equality – That the variance of data in the different groups should be the same
Your dependent variable – here, “weight”, should be continuous – that is, measured on a scale which can be subdivided using increments (i.e. grams, milligrams)

Independent Samples T Test

· Assumption of Independence: you need two independent, categorical groups that represent your independent variable. In the above example of test scores “males” or “females” would be your independent variable.

· Assumption of normality: the dependent variable should be approximately normally distributed. The dependent variable should also be measured on a continuous scale. In the above example on average test scores, the “test score” would be the dependent variable.

· Assumption of Homogeneity of Variance: The variances of the dependent variable should be equal.

Correlated Groups t Test

1. The dependent variable is quantitative and measured on an interval level

2. The independent variable is within subjects in nature

3. The independent variable has only two levels

orchestra answered 1 year ago

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