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Two-sample t-test

Two-sample t-test. Parameter … Let μ 1 represent the mean [ in context ] Let μ 2 represent the mean [ in context ] Hypotheses … H O : μ 1 - μ 2 = …. (usually 0) H A : [change = to <,>, or ≠ based on context]. Two-sample t-test. Assumptions/Conditions …

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Two-sample t-test

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  1. Two-sample t-test Parameter… Let μ1 represent the mean [in context ] Let μ2 represent the mean [in context ] Hypotheses… HO: μ1 - μ2 = …. (usually 0) HA: [change = to <,>, or ≠ based on context]

  2. Two-sample t-test Assumptions/Conditions… 1. 2 Indep SRS / RAT 3. Nearly Normal? 2. 10% cond. [check for both groups! ] Name the test… Two-sample t-test

  3. Two-sample t-test Test statistic… Find Find Obtain P-value… Sketch t-model and shade appropriately. To get df, use your calculator (STAT , TESTS, 2-SampTTest)

  4. Two-sample t-test Make a decision… Since P-value (…) is [less / greater] than α(…) I will [reject / fail to reject] the Ho State a conclusion IN CONTEXT!… There [is / is not] sufficient evidence to suggest that…[Ha in context]

  5. To “pool” or not to “pool”? Don’t pool. When you do this on the calculator, it will ask you if you want to ‘pool’ the data…. JUST SAY ‘NO’ ! “Pooling” in this case would indicate that you think the populations have equal variances.

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