A hypothesis is a prediction about a population. If the probability of the sample results occur by chance is low, then the hypothesis is supported; however, if the chances are high, the hypothesis is not supported.
The steps of hypothesis testing are to define the null and research hypothesis, determine the characteristics of the comparison distribution, establish a Z-cutoff score, calculate Z-scores, plot calculated Z-scores on the comparison distributions, and draw conclusions about the hypothesis.
Lowe defines and distinguishes between one and two-tailed tests. Examples of two- tailed and one- tailed tests are demonstrated.
Significance, in statistics, means the null hypothesis was rejected and the alternative hypothesis was supported. Significance is not due to chance.
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In this video lecture, Professor Naomi Lowe explains hypothesis testing (logic, process, one- and two-tailed tests, and significance in research).
Length: 43 minutes
Copyright date: ©2010
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Not available to Home Video and Publisher customers.
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