BUS 308 Week 5 Quiz Statistics for Managers (2019)
For a two-sample confidence interval, the interval shows the difference between the means.
A “small” sample size value means
An Effect size measure should be calculated when we fail to reject the null hypothesis, as it explains what influenced this decision was made.
The standard error term in the confidence interval formulas is an estimate of the variance of the measure the interval is created for.
While effect size measures are usually associated with particular tests, in theory they are interchangeable and any can be used with each test.
A small effect size result would argue against using the results of a test that found a statistically significant difference in any decision making.
One use of the effect size measure is to help us understand why the null hypothesis was not rejected.
One interpretation of the Effect Size measure is as an assessment of the impact switching from one variable to the on a result. For example, switching from being male to being female on a salary.
The values defining a large, medium, and small effect are similar across all effect size measures.
A confidence interval is generally created when statistical tests fail to reject the null hypothesis – that is, when results are not statistically significant.
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