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T-test Help

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  • #25344

    Brit
    Participant

    I have a company who provides survey data.  They use the t-test (assuming unequal variances) and have the following explanation of their results:
    When a score on a report is found to be significantly different from the score on the last report, the score is highlighted with one of the following symbols:
    +          95% certainty of significant increase (t >1.96).
    + +       99% certainty of significant increase (t >2.576).
    –           95% certainty of significant decrease (t< -1.96).
    – –         99% certainty of significant decrease (t< -2.576).
    Given that sample sizes and variances are different from report to report, does anyone have a problem with their reasoning?  Wondering why they do not use the test statistic and compare against the values from the t-test table given degrees of freedom.  I understand the z-table relationship, but think I would get different results.
    Help!

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    #61067

    Sheri
    Member

    One possibility may be that they are assuming they will have a large enough sample such that the t distribution begins to follow the normal distribution so they chose critical values from that distribution (1.96 & 2.576). ???
    Sheri

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    #61068

    Brit
    Participant

    You are correct. I found this was the case, however the population sample by quarter was too small for them to make the assumption. We have increased the sample size instead of reverting to the t tables for simplicity sake.

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