A Brief Quiz on Chapter 13
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When researchers choose an alpha risk of .05, they are revealing that five times out of a hundred they will claim statistical significance by chance alone.
In the logic of hypothesis testing, researchers attempt to find evidence to prove their research hypotheses.
Probability is the frequency that an event occurs in the population.
The critical region is the portion of a probability distribution which, if a test statistic falls in that zone, will cause researchers to claim to have found a "significant relationship."
A "significant difference" is identified as one that holds importance for researchers.
Alpha risk is the probability of committing a Type II error.
The central limit theorem tells us that sampling distributions become normal as the sample size increases.
Power is the probability of rejecting the null hypothesis correctly.
If sample sizes are equal, the effects of violating the assumption of homogeneous variances are trivial.
The standard error of the mean is an index of the probable mistakes made when estimating data points.
The t test for independent samples is used to compare the mean differences in two scores for each individual in the sample.