T3WB Understanding Statistical Power (PSYC2010)

Which of the following actions decreases the likelihood of committing a Type II error?

Power is the probability of failing to reject a false null hypothesis.

Define statistical power in the context of hypothesis testing. Explain its significance in research.

The statistical effect, denoted as ______, combines effect size and sample size to determine how easy it will be to find a real difference in a study.

Match the following terms with their definitions.

How does increasing the alpha level (e.g., from 0.01 to 0.05) typically affect statistical power, assuming all other factors remain constant?

A smaller effect size necessitates a larger sample size to achieve the same level of statistical power, assuming all other factors are held constant.

Explain how the concept of overlap between the null and alternative distributions relates to effect size and statistical power.

An effect size of d = 0.8 is conventionally considered a ______ effect size, according to Cohen's benchmarks.

Match the following effect sizes (Cohen's d) with their corresponding % overlap between the null and alternative distributions.

According to Cohen's conventions, what is the primary advantage of effect size as a measure in research?

The statistical effect (δ) is solely determined by the effect size (d) and does not take sample size (N) into account.

Explain the role of power tables in determining the required sample size for a study. What values are typically needed to use a power table effectively?

To calculate the sample size (N) needed to achieve a given power, one must first estimate the ______ and look up the corresponding statistical effect (δ) in a power table.

Match each step with the correct order to calculate power:

Why is it important to round up to the next whole number when calculating the required sample size for each group in a study?

In an independent samples t-test, the effect size is calculated differently than in a single-sample t-test, requiring a different formula.

Explain the importance of considering the number of tails (one-tailed vs. two-tailed) when using power tables, and how it affects the required sample size.

In the statistical effect formula, $ \delta = d \sqrt{N} $, 'd' represents the ______, while 'N' signifies the number of participants.

Match the researcher’s action to the respective experimental impact.

In statistical hypothesis testing, what does a high power indicate about a study?

If a study has low statistical power, it is more likely to produce real effects because the threshold for significance is lower.

How does the overlap between the null and alternative distributions relate to a study's ability to detect a real effect, and how might this be influenced by sample size?

Effect size measures how ______ the difference is between groups using standard deviation units.

Match each measure with what it reflects in research:

In a memory pill study, if the control group averages 70, the pill group averages 75, and the standard deviation is 10, what is the effect size (d)?

According to Cohen’s guidelines, a d-value of 0.5 is considered a small effect.

If a researcher is testing a new memory pill and wants to ensure that they have an 80% chance of finding the effect if it is really there, what does this statement mean in terms of statistical power?

Power is defined as the probability of making a decision to correctly ______ the null hypothesis and accept the alternative hypothesis when a real difference or relationship exists.

Match the following effect sizes with their description

Which of the following is NOT a factor that affects statistical power?

Effect size (d) is a measure of the degree to which Ho and H₁ are expected to differ and depends on the sample size.

Explain how increasing sample size influences statistical power, considering the relationship between Type II error and the detection of real effects.

If you don’t know the real effect size, use ______'s guidelines.

Match effect size guidelines to sample size for one-sample t test (alpha=0.05, two-tailed, power=0.80)

According to Cohen’s guidelines for effect sizes, which of the following indicates the amount the null and alternative groups overlap the least?

Estimating the probability to reject/accept the null hypothesis doesn’t depend on sample size.

Describe three key factors influencing statistical power and explain how each factor can be adjusted to enhance a study's ability to detect a true effect.

The statistical effect, often symbolized by the symbol ______, is a crucial element in determining probability.

Match the following steps to calculate power:

If a researcher aims to design a study with 80% power to detect a medium effect size using an independent groups t-test, and has a two-tailed alpha of 0.05, approximately how many participants per group would be required according to Cohen's conventions?

Statistical power represents the probability of failing to reject a false null hypothesis.

A researcher is planning a study and wants to ensure it has sufficient power. List three factors the researcher should consider that directly influence the power of a statistical test.

The statistical effect, often denoted as ______, combines effect size and sample size to determine the ease of finding a real difference in a study.

Match the following effect sizes (Cohen's d) with their corresponding percentage of overlap between the null and alternative distributions: