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Hypothesis Testing- a statistical method that uses sample data to evaluate…
Hypothesis Testing- a statistical method that uses sample data to evaluate a hypothesis about a population.
Hypotheses
Null Hypothesis- states that in the general population there is no change, no difference, or no relationship. In the context of an experiment. It predicts that the independent variable (treatment) has no effect on the dependent variable (scores) for the population.
Alternative Hypothesis- states that there is a change, a difference, or a relationship for the general population. It predicts that the independent variable (treatment) does have an effect on the dependent variable.
Alpha Level- or the level of significance, is a probability value that is used to define the concept of “very unlikely” in a hypothesis test.
Critical Region- composed of the extreme sample values that are very unlikely (as defined by the alpha level) 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 in the critical region, the null hypothesis is rejected.
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Errors
Type 1 Error- occurs when a researcher rejects a null hypothesis that is actually true. In a typical research situation, a Type I error means the researcher concludes that there is evidence for a treatment effect when in fact the treatment has no effect.
Alpha Level- the probability that the test will lead to a Type I error. That is, the alpha level determines the probability of obtaining sample data in the critical region even though the null hypothesis is true.
Type 2 Error- occurs when a researcher fails to reject a null hypothesis that is in fact 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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Statistical Tests
Statistically Significant- 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
Two-Tailed Test- comes from the fact that the critical region is divided between the two tails of the distribution. This format is by far the most widely accepted procedure for hypothesis testing.
One Tailed Test- the statistical hypotheses specify either an increase or a decrease in the population mean. That is, they make a statement about the direction of the effect.
Critical Region- defined by sample outcomes that are very unlikely to occur if the null hypothesis is true (that is, if the treatment has no effect).
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