HW#9.pdf - FA17 PSY 202 Section 4 HW#9 Conceptual section...

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FA17 PSY 202 Section 4 HW#9 Conceptual section What are the differences between a t-score and a z-score? A z-score measures the gap from the sample size and the null hypothesis. the size of the gap compares the standard error of estimation. In a T-score we don’t know the variance of the population, so as sample size increases, the distribution becomes more narrow Why can’t we use a z-test when our sample size is lower than 25? Because the critical values don’t work anymore, so it won’t be extreme enough if the sample size is small. How are the degrees of freedom for a t-distribution calculated? the degrees of freedom equal n-1, as it increases, it gets closer to normal distribution. What happens to the distribution’s kurtosis as those degrees of freedom increase? Kurtosis increases How does the increase in degrees of freedom affect the distribution’s variance? The variance decreases How does the increase in degrees of freedom affect the distribution’s critical values? The critical values become closer together What are the assumptions that must be met for us to use a t-test? the sample size doesn’t matter, continuos scores, approx. normal raw scores To determine the minimum sample size to use for a t-test, what information do we need ahead of time? when the skewness between +/- 2 and kurtosis less than 5 For what type of distribution do we need to use proportion tests instead of t-tests?
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