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Reliability does not imply validity.That is, a reliable measure that is measuring something consistently is not necessarily measuring what is supposed to be measured.
Statistical conclusion validity is the degree to which conclusions about the relationship among variables based on the data are correct or 'reasonable'. This began as being solely about whether the statistical conclusion about the relationship of the variables was correct, but now there is a movement towards moving to 'reasonable' conclusions ...
Often discussed in tandem with KR-20, is Kuder–Richardson Formula 21 (KR-21). [4] KR-21 is a simplified version of KR-20, which can be used when the difficulty of all items on the test are known to be equal.
Quantitative Data Analysis with IBM SPSS 17, 18 and 19: A Guide for Social Scientists. New York: Routledge. ISBN 978-0-415-57918-6. Levesque, R. (2007). SPSS Programming and Data Management: A Guide for SPSS and SAS Users (4th ed.). Chicago, Illinois: SPSS Inc. ISBN 978-1-56827-390-7. SPSS 15.0 Command Syntax Reference. Chicago, Illinois: SPSS ...
Predicted reliability, ′, is estimated as: ′ = ′ + ′ where n is the number of "tests" combined (see below) and ′ is the reliability of the current "test". The formula predicts the reliability of a new test composed by replicating the current test n times (or, equivalently, creating a test with n parallel forms of the current exam).
Cronbach's alpha (Cronbach's ), also known as tau-equivalent reliability or coefficient alpha (coefficient ), is a reliability coefficient and a measure of the internal consistency of tests and measures.
Previously when assessing a dataset before running a linear regression, the possibility of outliers would be assessed using histograms and scatterplots. Both methods of assessing data points were subjective and there was little way of knowing how much leverage each potential outlier had on the results data.
Bartlett's test is used to test the null hypothesis, H 0 that all k population variances are equal against the alternative that at least two are different. If there are k samples with sizes and sample variances then Bartlett's test statistic is