alpha
The Greek letter a, which symbolizes the criterion, the size of the region of rejection of a sampling distribution, and the theoretical probability of making a Type I error
alternative hypothesis
The statistical hypothesis describing the population parameters that the sample data represent if the predicted relationship does exist
beta
The Greek letter B, which letter symbolizes the theoretical probability of making a Type II error
experimental hypotheses
Two statements made before a study is begun, describing the predicted relationship that may or may not be demonstrated by the study
inferential statistics
Procedures for determining whether sample data represent a particular relationship in the population
nonparametric statistics
Inferential procedures that do not require stringent assumptions about the parameters of the raw score population represented by the sample data; usually used with scores most appropriately described by the median or the mode
nonsignificant
Describes results that are considered likely to result from chance sampling error when the predicted relationship does not exist; it indicates failure to reject the null hypothesis
null hypothesis
The statistical hypothesis describing the population parameters that the sample data represent if the predicted relationship does not exist
one-tailed test
The test used to evaluate a statistical hypothesis that predicts that scores will only increase or only decrease
parametric statistics
Inferential procedures that require certain assumptions about the parameters of the raw score population represented by the sample data; usually used with scores most appropriately described by the mean
power
The probability that a statistical test will detect a true relationship and allow the rejection of a false null hypothesis
significant
Describes results that are too unlikely to accept as resulting from chance sampling error when the predicted relationship does not exist; it indicates rejection of the null hypothesis
statistical hypothesis
Two statements (H0 and Ha) that describe the population parameters the sample statics will represent if the predicted relationship exists or does not exist
two-tailed test
The test used to evaluate a statistical hypothesis that predicts a relationship, but not whether scores will increase or decrease
Type I error
A statistical decision-making error in which a large amount of sampling error causes rejection of the null hypothesis when the null hypothesis is true (that is, when the predicted relationship does not exist)
Type II error
A statistical decision-making error in which the closeness of the sample statistic to the population parameter described by the null hypothesis causes the null hypothesis to be retained when it is false (that is, when the predicted relationship does exist)
z-test
The parametric procedure used to test the null hypothesis for a single-sample experiment when the true standard deviation of the raw score population is known
