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Understanding Sampling Errors in Statistical Analysis

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Learn about differences among samples, errors in sampling, and significant differences attributed to an external factor. Discover the outcomes of statistical tests, correct and incorrect decisions, Type 1 and Type 2 errors in data analysis.

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Understanding Sampling Errors in Statistical Analysis

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  1. Differences Amongst Samples • Sampling Error – differences between two samples that are attributed to random error or chance • Significant Differences – differences between two samples that are attributed to an outside factor such as an IV

  2. Decisions • There are four possible outcomes after conducting a statistical test

  3. Correct Decisions • When the null is retained we expect the following to be the case • When the null is rejected we expect the following to be the case

  4. Type 1 Error • A type 1 error occurs when two samples appear to be different, but are actually from the same population

  5. Type 2 Error • Type 2 errors occur when two samples appear to be from the same population, but are actually from different populations

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