Exam 12: Confidence Intervals and Effect Size: Building a Better Mousetrap

A doctor is examining differences between two treatments. He calculated a 95% confidence interval on the mean difference between the two groups. The interval ranged from -1.2 to 3.48. What does this suggest?

The population average for number of children per household is 2.4 in a particular country with a standard deviation of 1.1. A research is conducting research in a neighborhood that has relatively low socioeconomic status. Her sample of 40 families averages at 3.3 children. what does the confidence interval tell you?

Partial eta-squared are only used for factorial ANOVAs, and not one-way ANOVAs.

Like an inferential test, confidence intervals can be calculated on mean differences to test for statistical significance..

When calculating a confidence interval for a independent samples t-test instead of a one-sample t-test, which of the following best describes the difference in their calculations?

A 99% confidence interval is ____________ than a 95% confidence interval

Suppose that the population mean for IQ is 100 with a standard deviation of 15. A researcher is testing a group 25 of talented youth. His sample has a mean of 112 with a standard deviation of 14. What does the CI tell us about the sample of young talented youth?

Use the source table below to answer the following questions Source SS df MS F Factor 1 8819 1 Factor 2 27482 2 Factor 1 * Factor 2 17334 2 Error 55827 35 Calculate each eta-squared

A t-test found a significant effect in which one condition had a detrimental effect on the outcome, making it significantly worse. In this case, one would expect that Cohen's d would be negative.

With respect to the value of Cohen's d, effects that are small are near 0, and effects that are considered large must be greater than 1.

Which of the following most accurately describes A 95% confidence interval of a mean?

How do point estimates compare to confidence intervals?

In a 3 x 4 ANOVA, how many partial eta-squared could one calculate?

A researcher collects a sample of individuals' productivity by measuring the number of words they typed in an hour during a writing session with 20 individuals. The sample mean is 1738.2 words this week. The individuals from last week's 20 individuals only had a mean of 1553.7 words. The pooled variance is 11545.9. Calculate the Cohen's d for this mean difference.

Which of the following reasons best explains the value of effect sizes?

The researcher calculates a 95% confidence interval for the mean difference. 0 is not captured in the interval. What would this suggest?

If an IV has a significant effect on a DV, then the effect size must be large

One reason why effect sizes are generally omitted is because it makes the statistics harder to understand and does not provide any additional information that significance testing doesn't already tell us.

Eta-squared cannot be greater than 1.00.

If you construct a 95% confidence interval around a sample mean and the 95% CI does not include the population mean, what would this suggest?