Effect size and power
Understanding Effect Size and Power
Test your knowledge on effect sizes and statistical power with this challenging quiz! This quiz consists of 10 questions that will deepen your understanding of key concepts in statistics and research methodology.
- Multiple choice questions
- Assess your understanding of odds ratios, effect sizes, and statistical measures
Odds ratios are calculated:
By dividing the odds of an event happening in those exposed to an intervention by the odds of an event happening in those not exposed to the intervention
By dividing the odds of an event happening in those exposed not to an intervention by the odds of an event happening in those exposed to the intervention
By multiplying the odds of an event happening in those exposed not to an intervention for the odds of an event happening in those exposed to the intervention
By multiplying the odds of an event happening in those exposed to an intervention for the odds of an event happening in those not exposed to the intervention
None of the above
Suppose a botanist applies two different fertilizers to plants to determine if there is a significant difference in average plant growth (in inches) after one month. A month later, running a statistical analysis, he notices that d=0.92 Therefore, he concludes that there is a small effect size. Is the botanist correct?
True
False
Which is the right order?
No correlation, weak positive correlation, strong negative correlation, weak negative correlation, moderate negative correlation, strong positive correlation
Strong positive correlation, weak positive correlation, strong negative correlation, weak negative correlation, moderate negative correlation, no correlation
Weak negative correlation, strong negative correlation, no correlation, strong positive correlation, weak positive correlation, moderate negative correlation
Weak negative correlation, moderate negative correlation, no correlation, strong positive correlation, weak positive correlation, strong negative correlation
1. Which of the below is NOT a way to increase the power of a statistic:
Increase sample size
Reduce measurement error
Increase effect size
Decrease type II error
What is the difference between Eta and partial eta squared?
Partial eta only looks at the sample population
Partial eta considers the means rather than variance between groups
Partial eta considers the variance attributed to one variable relative to others
Eta squared is only to be used for ANCOVA
Why is Omega squared a less biased measure of effect size?
It considers the variance of the model and the average variance in the population
It considers group means instead of variance
It is useful for contrasts
It can be used for two sided hypotheses
What influence can a larger sample size have on effect size and Power?
Decreased power, decreased effect size
Increased power, decreased effect size
Decreased power, Increased effects size
Increased power, increased effect size
What is considered a large effect size for cohen’s f:
0.10
0.95
0.05
0.40
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