• Thank u ravi
    And for @CFB what i want is to do analysis for discrete data, if you know how to go about do pour in you immense knowledge as i arent that intelligent or grammatically correct as u are .I know how to go about for continuous data if u can be of any help concerning discrete data about how to go about collect, analyze, and report using …[Read more]

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  • For a two sided test the null is indeed mean1 = mean2 and the alternative is that mean1 is not equal to mean2. This is reasonable because the two sided test is checking for changes in both directions. In a one sided test you are only interested in deviations in a single direction therefore the null can’t be stated as mean1 = mean2 because you…[Read more]

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  • @robert – thanks for your comments. Maybe I should provide a bit more clarity. I’m more concerned about more common hypothesis tests such as 2 Means t-tests (2 Sample t), 2 Propotions, etc. Equivalence testing is its own beast. And maybe there is confusion (likely on my part) as I don’t think a 2 Means t-Test with Ho: Sample 1 = Sample 2 and…[Read more]

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  • Equivalence testing is not the same thing as a one sided test. Therefore = is not an acceptable choice for the null. All of my references state that, for a one sided test, the null is either <= or >= and the alternative is either > or <.

  • So here is an interesting topic…. The Null Hypothesis Statement when conducting a one sided test.

    Should it be written as a statement of equality (=)

    OR

    should the Null be expressed as composite (<= or >=)?

    From my understanding neither is wrong. I’m just trying to figure out from this fine group what is the most common…[Read more]

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