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Business 205

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Review Survey Designs Survey Ethics

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Preview Assumptions of Tests Two Group Independent Sample T-test

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Which test do you use? You know the mean of the sample, mean of the population but not the standard deviation of the population. You know the mean of the sample, mean of the population and the standard deviation of the population.

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Example You are a CEO and want to know what effect interactions with people has on their job satisfaction ratings. You choose manager A’s group and manager B’s group to compare. Manager A never interacts with the group he supervises while Manager B is always interacting with the group he supervises.

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Assumptions for a 2-Group T-test 2 samples are randomly selected in an independent manner from the two target populations Sampling distribution is approximately normal Mean population difference = 0

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Hypothesis H1: A manager’s interaction levels has an effect on an employee’s job satisfaction levels. Is this 1 or 2 tailed? What is the null? What is the mathematical/symbolical hypotheses for the H1 and H0?

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Symbolically Two-tailed (“has an affect”) You are saying that the differences between the two samples are going to be (something) to the differences between the two populations H1: Mean sample1 – Mean sample2 ≠ 0 Null: Mean sample1 – Mean sample2 = 0 α=.05

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2 Independent Sample T-tests DEGREES FREEDOM df1 = (n1 – 1) df2 = (n2 – 1) dftotal = df1 + df2 Pooled Variance =

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2 Independent Sample T-tests Standard Error = Ind 2 T-test =

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Data on job satisfaction df total = 9 + 9 = 18 df A = 10 – 1 = 9 df B = 10 – 1 = 9 t critical = ± 2.101 Group A (no interaction) Group B (interacts) 2418 2319 1623 1729 1930 1331 1729 2026 1521 2624

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Calculations Sums of Squares: SS A = 160 SS B = 200 Pooled Variance: V P = = 20

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Calculations Estimated Standard Error: SE = T-statistic (t-test): t =

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Findings T = - 3.00 t critical = ± 2.101 Conclusion: Accept your hypotheses; it is significant. Some researchers will say that the group with more interaction (Group B) reports higher job satisfaction levels. M A = 19M B = 25 -2.101 2.101

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Scenario Example A manager wants to know if employees who have a female manager are more satisfied than those with a male manager. What it the IV and DV? What is the hypothesis? Is this 1 or 2 tailed? What is the null? What is the mathematical/symbolical hypotheses for the H1 and H0?

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Data on job satisfaction df total = df A = df B = t critical = Group 1 female manager Group 2 Male manager 52 45 42 33

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Calculations Sums of Squares: SS 1 = SS 2 = Pooled Variance: V P =

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Calculations Estimated Standard Error: SE = T-statistic (t-test): t =

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Findings T = t critical = Conclusion:

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