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Session 2 Introduction to compare mean

Session 2 Introduction to compare mean. Dr. Tu Van Binh. Compare means and test. Compare means Independent samples T test: two independent groups Paired samples T test: Paired variables Comparing more than two independent groups: Analysis of Variance (ANOVA) or Kruskal Wallis test.

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Session 2 Introduction to compare mean

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  1. Session 2Introduction to compare mean Dr. Tu Van Binh

  2. Compare means and test • Compare means • Independent samples T test: two independent groups • Paired samples T test: Paired variables • Comparing more than two independent groups: Analysis of Variance (ANOVA) or Kruskal Wallis test https://statistics.laerd.com/statistical-guides/independent-t-test-statistical-guide.php https://statistics.laerd.com/spss-tutorials/independent-t-test-using-spss-statistics.php

  3. Compare means and test • Calculate means of values, percent • Show different between two groups • Test significant differences • Significant level • Value of Sig. < 0.01  Significant at 1% • 0.01 ≤ Value of Sig. < 0.05  Significant at 5% • 0.05 ≤ Value of Sig. < 0.1  Significant at 10%

  4. Compare means - SPSS • File: dataspss2.2-Electronic • Compare two groups of male and female with satisfaction on Electronic Supermarkets (Q9) (Q9.1) • Discussion on empirical result • Conclusion how different between two groups

  5. Manual Guide

  6. Empirical result Where to check significant

  7. Samples of hypothesis Prob.1 H0: The income of male is equal to that of female; H1: Reject H0 H0: The energy (working hours) of female is equal to that of male H1: Reject H0 Prob.2 H0: Sleeping hours of male and female are the same H1: Reject H0 Prob.3

  8. Level of Significance:and the Rejection Region H0: 1-= non-rejection region H0: Ha: /2 = Rejection region /2 = Rejection region Two-tail test 0 H0: 1-= non-rejection region H0: Ha:  = Rejection region Upper-tail test 0 H0: H0: Ha: 1-= non-rejection region  = Rejection region Lower-tail test 0  = level of significance = Critical Value

  9. One-tailed test Two tailed test Large sample test of hypothesis H0: H0: Ha: Ha: Where D0 = Hypothesized difference between the means (this is often 0) Test statistic: Test statistic: Where is the standard deviation of sample 1, is of the SD of sample 2 Rejection region: Rejection region: Table value Table value or Assumption: Zα table value: df. = n1+ n2 – 1 (file table enclosed) Confident interval = (1- α)

  10. Formula for sample standard deviation • Note: Square of sample standard deviation is sample variance

  11. Conclusion • There is an evident difference in revenue between service and industry • Or there is a significant difference at 5 percent level in revenue between service and industry • Of which the revenue of service is significantly higher than that of industry.

  12. PracticeFile: CFVG MMSS9 student sample • Compare means of “sleeping hours” between married student and single student • Apply t-test to test a difference in mean values of sleeping hours between married and single students • Discussion

  13. PracticeFile: dataspss2.1 • Compare means of export values of small size company and large size company (Q208 by Q2group). • Apply t-test to test a difference in mean values of exporting companies between those two groups above • Discussion and conclusion

  14. Group Assignment • File: • MCCdata.xls (raw data) • MCC-questionnaire.xls (questionnaire) • Questions concerned: Q3, Q4, Q8, Q11, Q12, Q14, Q15, Q16, Q17, Q18, Agegroup. • Assignment: Groups select at least 4 variables (4 variable) to present results of “descriptive analysis), and discuss output • Think Frequency and Crosstab; compare mean

  15. Paired-Samples T-Test of Population Mean Differences • The same observation • Two variables compared are seemly the same kind of things that we want to compare • Compare between two periods, or between two characteristics, etc • File: dataspss2.2-Electronic

  16. Practice :file: QUESTIONNAIRE-Electronic ; File: data-Electronic • Paired sample t-test • Nguyen Kim (Q9.5) vs. IDEAS (Q9.1) • Nguyen Kim (Q9.5) vs. Phan Khang (Q9.2) • Nguyen Kim (Q9.5) vs. Thien Hoa (Q9.3) • Nguyen Kim (Q9.5) vs Cho Lon (Q9.4) • Conclusion

  17. Solving the problem with SPSS: The paired-samples t-test - 1 Having satisfied the level of measurement and assumption of normality, we now request the statistical test. Select Compare Means > Paired-Samples T Test… from the Analyze menu.

  18. Analysis of Variance (ANOVA) • Comparing more than two independent groups: Analysis of Variance (ANOVA) or Kruskal Wallis test

  19. Test three groups by ANOVA H0: H1: At least two treatment means differ Assumptions: • All p population probability distribution are normal • The p population variances equal • Samples are selected randomly and independently from respective populations

  20. Application to test satisfaction on supermarkets (Q9) regarding to income (Q19) • Identify groups available • ANOVA test

  21. Manual Guide

  22. Group practice • Each group checks its owned database • Select two categorical variables • Compare some variables • Interpreting output

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