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Decision Making (2 Samples) 1. Introduction of 2 samples 2.

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Presentation on theme: "Decision Making (2 Samples) 1. Introduction of 2 samples 2."— Presentation transcript:

1 Decision Making (2 Samples) 1

2 Introduction of 2 samples 2

3 5-2 Inference on the Mean of 2 population, Variance known 3

4 Inference on the Mean of 2 population, Variance known 4

5 Ex: Drying time of primer has SD=8 min. 10 Samples of Primer1has x-bar1=121 min. and another 10 samples of Primer II has x-bar2=112 min. Is the primer 2 has effect to drying time. H0:  1-  2=0H1:  1-  2>0 n1=n2  1=  2 Z0=2.52 P=1-  (2.52)= <0.05 Then reject H0 5

6 Sample size 6

7 5-3 Inference on the Mean of 2 population, Variance unknown 7

8 Case I: Equal variances (Pooled t-test) 8

9 9

10 H0:  1-  2=0H1:  1-  2≠0 n1=n2=8  1=  2 T0=-0.35 P=0.729 > 0.05 Then accept H0 Two-Sample T-Test and CI: C5, C8 N Mean StDev SE Mean C C Difference = mu (C5) - mu (C8) Estimate for difference: % CI for difference: (-3.37, 2.42) T-Test of difference = 0 (vs not =): T-Value = P-Value = DF = 14 Both use Pooled StDev =

11 11

12 5-3 Inference on the Mean of 2 population, Variance unknown 12

13 13

14 H0:  1-  2=0H1:  1-  2≠0 n1=n2=10  1 ≠  2 T0=-2.77 P=0.016 < 0.05 Then reject H0 Two-Sample T-Test and CI: Metro, Rural N Mean StDev SE Mean Metro Rural Difference = mu (Metro) - mu (Rural) Estimate for difference: % CI for difference: (-26.71, -3.29) T-Test of difference = 0 (vs not =): T-Value = P-Value = DF = 13 14

15 15

16 5-4 Paired t-test A special case of the two-sample t-tests of Section 5-3 occurs when the observations on the two populations of interest are collected in pairs. Each pair of observations, say (X 1j, X 2j ), is taken under homogeneous conditions, but these conditions may change from one pair to another. For example; The test procedure consists of analyzing the differences between hardness readings on each specimen. 16

17 Paired t-test 17

18 18

19 H0:  D =  1-  2=0H1:  D =  1-  2≠0 n1=n2=9  1 ≠  2 T0=6.08 P=0.000 < 0.05 Then reject H0 Paired T-Test and CI: Karlsruhe method, Lehigh method N Mean StDev SE Mean Karlsruhe method Lehigh method Difference % CI for mean difference: (0.1700, ) T-Test of mean difference = 0 (vs not = 0): T-Value = 6.08 P-Value =

20 5-6 Inference on 2 population proportions 20

21 Inference on 2 population proportions 21

22 H0: p1=p2H1: p1≠p2 Z0=5.36 P=0.000 < 0.05 Then reject H0 Test and CI for Two Proportions Sample X N Sample p Difference = p (1) - p (2) Estimate for difference: % CI for difference: ( , ) Test for difference = 0 (vs not = 0): Z = 5.36 P-Value =


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