The degrees of freedom (df) equation for single sample t-tests (both sigma known

Question

The degrees of freedom (df) equation for single sample t-tests (both sigma known and unknown) is The degree of freedom (df) equation for match/related samples t-tests is The degrees of freedom (df) equation for independent sample t-tests can be written as or meaning the samples can be of different sizes. One important assumption underlying t-tests is that both samples have equal (or at least similar) You've recently started online dating and found a potential match that you're extremely interested in pursuing. After showing a close friend your match's profile, your friend tells you that it won't ever work-your astrological signs are complete opposites! You are Aries and your match is a Libra. Given the following information, determine if these two signs differ significantly in terms of average personality test scores. The test hast values that range from 35 to 380, where higher scores are associated with "type A" personalities and lower scores with "type B" personalities. Use alpha =.05. Estimate of the standard error of the difference between means = 11.52 What is the null hypothesis for this type of test? What is your critical value? What is the your calculated test statistic? What will your decision about the hypotheses be: Starting with a two-tailed test at a =.05, at what level of significance (a-level) will you find the same critical values in a one-tailed test(i.e. at what level of significance do you find a t-value of 1.96 in a one-tailed test)?

Explanation / Answer

1.

df = n - 1 [ANSWER]

where n = the sample size.

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2.

df = m - 1 [ANSWER]

where m = the number of pairs.

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3.

df = (n1 - 1) + (n2 - 1) OR n1 + n2 - 2 [ANSWER]

where n1, n2 = the sample sizes of the two groups.

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