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21 Cards in this Set
- Front
- Back
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hypothesis test
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a statistical method that uses sample data to evaluate a hypothesis about a population. the purpose of the hypothesis test is to rule out chance (sampling error) as a cause for the results from a research study
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null hypothesis
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states that in the general population there is no change, no difference, or no relationship. in the context of an experiment, the null hypothesis predicts that the independent variable (treatment) *has no effect* on the dependent variable for the population
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alternative hypothesis
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states that there is a change, a difference, or a relationship for the general population. in the context of an experiment, this predicts that the independent variable treatment does have an effect on the dependent variable
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alpha level / level of significance
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a probability value that is used to define the very unlikely sample outcomes if the null hypothesis is true
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critical region
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is composed of extreme sample values that are very unlikely to be obtained if the null hypothesis is true. the boundaries for the critical region are determined by the alpha level. if sample data fall into the critical region, the null hypothesis is rejected
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Type 1 error
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this occurs when a researcher rejects a null hypothesis that is actually true. typically, a type 1 error means that the researcher concludes that a treatment does have an effect when in fact it has no effect
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Alpha level for a hypothesis test
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this is the probability that the test will lead to a Type 1 error. that is, the alpha level determines the probability of obtaining sample data in the critical region even though the null hypothesis is true.
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Type II error
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this occurs when a researcher fails to reject a null hypothesis that is really false. in a typical research situation, a type II error means that the hypothesis test has failed to detect a real treatment effect
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Statistically significant
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a result is said to be statistically significant if it is very unlikely to occur when the null hypothesis is true. that is, the result is sufficient to reject the null hypothesis. thus a treatment has a significant effect if the decision from the hypothesis test is to reject the null hypothesis.
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statistical significance
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a result is said to be significant or statistically significant if it is very unlikely to occur when the null hypothesis is true. that is, the result is sufficient to reject the null hypothesis. thus a treatment has a significant effect if the decision from the hypothesis test is to reject the null hypothesis.
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directional hypothesis test / one-tailed test
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the statistical hypotheses H0 and H1 specify either an increase or a decrease in the population mean score. that is, they make a statement about the direction of the effect.
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effect size
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a measure of effect size is intended to provide a measurement of the size of the sample(s) being used
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level of significance
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the level of significance is the alpha level, which measures the probability of a type 1 error
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test statistic
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a statistic that summarizes the sample data in a hypothesis test. the test statistic is used to determine whether or not the data are in the critical region
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beta
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beta is the probability of a TYPE II error
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directional one-tailed test
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hypothesis test that places the critical region entirely in one tail of the distribution and includes a directional prediction in the hypothesis statement
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effect size
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a measure of the size of the treatment effect that is separate from the statistical significance of the effect
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power
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the probability that the hypothesis will reject the null hypothesis when there actually is a treatment effect
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What are the boundaries of the critical region for alpha=.05
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+/- 1.96
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What are the boundaries of the critical region for alpha=.01
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+/-2.58
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Cohen's d: magnitude of d
What are small, medium and large effect sizes? |
d=.2 (small effect size)
d=.5 (medium effect size) d=.8 (large effect size) |
