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Thorne and Giesen Book Cover
Statistics for the Behavioral Sciences, 4/e
Michael Thorne, Mississippi State University -- Mississippi State
Martin Giesen, Mississippi State University -- Mississippi State

Confidence Intervals and Hypothesis Testing

Definitions


sampling distribution of means  distribution whose scores are means drawn from some population
parent population  the population from which the sample is drawn
central limit theorem  in simplified form, the idea that as sample size increases, the resulting sampling distribution of means more closely approximates the normal distribution
standard error of the mean  standard deviation of the sampling distribution of means
degrees of freedom  number of values free to vary after certain restrictions are placed on the data
estimated standard error of the mean  estimated standard deviation of the sampling distribution of means
t distribution  probability distribution of t scores, which are estimated z scores
confidence interval  range of values within which malmost certainly lies
critical values of t  values of t cutting off deviant portions of the t distribution
interval estimate  estimating a range of values rather than a specific value for a population parameter; the confidence interval is an example of an interval estimate
null hypothesis  in hypothesis testing, the hypothesis that assumes a particular value for a population parameter
alternative hypothesis  in hypothesis testing, the hypothesis that the value of a population parameter is a value other than we have assumed it to be in the null hypothesis
nondirectional hypothesis  an alternative to the null hypothesis that states that the population parameter is not equal to the value specified by the null hypothesis
directional hypothesis  alternative hypothesis that states the direction of the difference between a population parameter and the value assumed by the null hypothesis
significant  in statistics, a term indicating rejection of the null hypothesis
alpha level  the probability level at which the null hypothesis is tested
rejection rule  the rule that states the conditions under which the null hypothesis will be rejected or will fail to be rejected
Type I error  rejecting a true null hypothesis
Type II error  failing to reject a false null hypothesis
power  the probability that a test will reject a false null hypothesis
meta-analysis  procedure using the effect size to analyze the research results from large numbers of studies
effect size  the size of the difference between the null hypothesis and the alternative hypothesis in standardized units