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INTRO TO HYPOTHESIS TESTING:
a statistical method that uses sample data…
INTRO TO HYPOTHESIS TESTING:
a statistical method that uses sample data to evaluate a hypothesis about a population.
WHY USE A HYPOTHESIS TEST?:
typically used in the context of a research study. That is, a researcher completes a research study and then uses a hypothesis test to evaluate the results.
ELEMENTS OF A HYPOTHESIS TEST:
known, population, unknown population, and sample in the research study
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FOUR STEPS OF. A HYPOTHESIS TEST:
outline the hypothesis-testing procedure that allows us to use sample data to answer questions about an unknown population.
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STEP 2: SET THE CRITERIA FOR A DECISION: Eventually the researcher will use the data from the sample to evaluate the credibility of the null hypothesis. The data will either be consistent with the null hypothesis or tend to refute the null hypothesis.
STEP 3: COLLECT DATA & COMPUTE SAMPLE STATISTICS:
Collect and summarize the sample data.
Calculate the appropriate test statistic (such as a z-score, t-score, chi-square statistic, etc.). Determine the p-value or compare the test statistic to a critical value, depending on the method being used.This step tells you how well the sample data aligns with the null hypothesis
ALPHA LEVEL OR LEVEL OF SIGNIFICANCE:
probability value that is used to define the concept of �very unlikely�
CRITICAL REGION: The extremely unlikely values, as defined by the alpha level,
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TEST STATISTIC: indicates that the sample data are converted into a single figure to test a hypothesis
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EFFECT SIZE:
intended to provide a measurement of the absolute magnitude of a treatment effect, independent of the size of the sample(s) being used
COHEN'S d:
One of the simplest and most direct methods for measuring effect size.Cohen (1988) recommended that effect size can be standardized by measuring the mean difference in terms of the standard deviation.