Overview of Inferential Statistics Flashcards
Statistical power refers to the ability to:
A. retain a null hypothesis.
B. retain a true null hypothesis.
C. reject a null hypothesis.
D. reject a false null hypothesis.
Answer D is correct. Statistical power refers to the ability to reject a false null hypothesis, which is ordinarily what a researcher wants to do.
The probability of making a Type II error equals which of the following?
A. alpha
B. beta
C. one minus alpha
D. one minus beta
Answer B is correct. The probability of making a Type II error is equal to beta which is not set by the researcher but can be reduced by increasing statistical power.
Bayes’ theorem allows researchers to update prior knowledge about a parameter using:
A. current (observed) data.
B. previous knowledge and current (observed) data.
C. qualitative information.
D. a revised theoretical framework.
Answer B is correct. Bayes’ theorem uses previous knowledge (the prior) and current data (the likelihood function) to derive updated knowledge about a parameter (the posterior).
The central limit theorem predicts that the sampling distribution of means increasingly approaches normal as the:
A. number of samples increases regardless of the shape of the population distribution.
B. size of the sample increases regardless of the shape of the population distribution.
C. number of samples increases only when the population distribution is normal.
D. size of the sample increases only when the population distribution is normal.
Answer B is correct. The central limit theorem predicts that the sampling distribution of means increasingly approaches a normal shape as the size of the sample increases, regardless of the shape of the population distribution of scores.
Changing alpha from .05 to .01:
A. increases the probability of making a Type I error and decreases the probability of making a Type II error.
B. decreases the probability of making a Type I error and increases the probability of making a Type II error.
C. increases the probability of making a Type I error and Type II error.
D. decreases the probability of making a Type I error and Type II error.
Answer B is correct. Knowing that changing the size of alpha has opposite effects on the chance of making a Type I and Type II error would have allowed you to eliminate answers C and D. Then knowing that a Type I error occurs when a true null hypothesis is rejected and that decreasing alpha makes it harder to reject a null hypothesis whether it is true or false would have helped you identify answer B as the correct answer: Decreasing alpha decreases the probability of making a Type I error (rejecting a true null hypothesis) and, conversely, increases the probability of making a Type II error (retaining a false null hypothesis).
A Type I error occurs when a researcher:
A. retains a true null hypothesis.
B. retains a false null hypothesis.
C. rejects a true null hypothesis.
D. rejects a false null hypothesis.
Answer C is correct. When a researcher rejects a true null hypothesis, the researcher has concluded that the independent variable has had a significant effect on the dependent variable, but the observed effect is actually due to sampling error or other factors. This type of incorrect decision is known as a Type I error.
To calculate the standard error of means you need which of the following?
A. sample mean and standard deviation
B. sample mean and sample size
C. population standard deviation and sample size
D. population mean and standard deviation
Answer C is correct. The central limit theorem predicts that the standard deviation of the sampling distribution (also known as the standard error of means) is equal to the population standard deviation divided by the square root of the sample size.
