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Section 9.4 Inferences About Two Means (Matched Pairs) Objective Compare of two matched-paired means using two samples from each population. Hypothesis Tests and Confidence Intervals of two dependent means use the t-distribution 1 Definition Two samples are dependent if there is some relationship between the two samples so that each value in one sample is paired with a corresponding value in the other sample. Two samples can be treated as the matched pairs of values. 2 Examples • Blood pressure of patients before they are given medicine and after they take it. • Predicted temperature (by Weather Forecast) and the actual temperature. • Heights of selected people in the morning and their heights by night time. • Test scores of selected students in Calculus-I and their scores in Calculus-II. 3 Example 1 First sample: weights of 5 students in April Second sample: their weights in September These weights make 5 matched pairs Third line: differences between April weights and September weights (net change in weight for each student, separately) In our calculations we only use differences (d), not the values in the two samples. 4 Notation d Individual difference between two matched paired values μd Population mean for the difference of the two values. n Number of paired values in sample d Mean value of the differences in sample sd Standard deviation of differences in sample 5 Requirements (1) The sample data are dependent (i.e. they make matched pairs) (2) Either or both the following holds: The number of matched pairs is large (n>30) or The differences have a normal distribution All requirements must be satisfied to make a Hypothesis Test or to find a Confidence Interval 6 Tests for Two Dependent Means Goal: Compare the mean of the differences H0 : μd = 0 H0 : μd = 0 H0 : μd = 0 H1 : μd ≠ 0 H1 : μd < 0 H1 : μd > 0 Two tailed Left tailed Right tailed 7 Finding the Test Statistic t= d – µd sd n Note: md = 0 according to H0 degrees of freedom: df = n – 1 8 Test Statistic Degrees of freedom df = n – 1 Note: Hypothesis Tests are done in same way as in Ch.8-5 9 Steps for Performing a Hypothesis Test on Two Independent Means • Write what we know • State H0 and H1 • Draw a diagram • Calculate the Sample Stats • Find the Test Statistic • Find the Critical Value(s) • State the Initial Conclusion and Final Conclusion Note: Same process as in Chapter 8 10 Example 1 Assume the differences in weight form a normal distribution. Use a 0.05 significance level to test the claim that for the population of students, the mean change in weight from September to April is 0 kg (i.e. on average, there is no change) Claim: μd = 0 using α = 0.05 11 Example 1 d Data: -1 -1 4 -2 1 H0 : µd = 0 H1 : µd ≠ 0 Two-Tailed H0 = Claim n=5 d = 0.2 t = 0.186 -tα/2 = -2.78 Sample Stats t-dist. df = 4 tα/2 = 2.78 sd = 2.387 Use StatCrunch: Stat – Summary Stats – Columns Test Statistic Critical Value tα/2 = t0.025 = 2.78 (Using StatCrunch, df = 4) Initial Conclusion: Since t is not in the critical region, accept H0 Final Conclusion: We accept the claim that mean change in weight from September to April is 0 kg. 12 Example 1 d Data: -1 -1 4 -2 1 Sample Stats H0 : µd = 0 H1 : µd ≠ 0 n=5 Two-Tailed H0 = Claim d = 0.2 sd = 2.387 Use StatCrunch: Stat – Summary Stats – Columns Stat → T statistics→ One sample → With summary Sample mean: 0.2 Sample std. dev.: 2.387 Sample size: 5 ● Hypothesis Test Null: proportion= 0 Alternative ≠ P-value = 0.8605 Initial Conclusion: Since P-value is greater than α (0.05), accept H0 Final Conclusion: We accept the claim that mean change in weight from September to April is 0 kg. 13 Confidence Interval Estimate We can observe how the two proportions relate by looking at the Confidence Interval Estimate of μ1–μ2 CI = ( d – E, d + E ) 14 Example 2 Sample Stats n=5 d = 0.2 tα/2 = t0.025 = 2.78 Find the 95% Confidence Interval Estimate of μd from the data in Example 1 sd = 2.387 (Using StatCrunch, df = 4) CI = (-2.8, 3.2) 15 Example 2 Sample Stats n=5 d = 0.2 Find the 95% Confidence Interval Estimate of μd from the data in Example 1 sd = 2.387 Stat → T statistics→ One sample → With summary Sample mean: 0.2 Sample std. dev.: 2.387 Sample size: 5 ● Confidence Interval Level: 0.95 CI = (-2.8, 3.2) 16