mgmt 276 statistical inference in management fall 2013 n.
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MGMT 276: Statistical Inference in Management Fall , 2013 PowerPoint Presentation
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MGMT 276: Statistical Inference in Management Fall , 2013

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MGMT 276: Statistical Inference in Management Fall , 2013

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  1. MGMT 276: Statistical Inference in ManagementFall, 2013 Welcome

  2. Please read: Chapters 10 – 12 in Lind book and Chapters 2 – 4 in Plous book: (Before the next exam – November 14th) Lind Chapter 10: One sample Tests of Hypothesis Chapter 11: Two sample Tests of Hypothesis Chapter 12: Analysis of Variance Plous Chapter 2: Cognitive Dissonance Chapter 3: Memory and Hindsight Bias Chapter 4: Context Dependence

  3. Exam 3 – Thursday (11/14/13) Study guide online Bring 2 calculators (remember only simple calculators,we can’t use calculators with programming functions) Bring 2 pencils (with good erasers) Bring ID We’ve added new tutoring opportunities Please see website for schedule of TA office hours

  4. Exam 2 – Thursday (11/14/13) Study guide online Bring 2 calculators (remember only simple calculators,we can’t use calculators with programming functions) Bring 2 pencils (with good erasers) Bring ID We’ve added new tutoring opportunities Please see website for schedule of TA office hours

  5. No homework due Just study for Exam 3 Please click in My last name starts with a letter somewhere between A. A – D B. E – L C. M – R D. S – Z Please double check – All cell phones other electronic devices are turned off and stowed away

  6. Use this as your study guide By the end of lecture today11/12/13 • Logic of hypothesis testing • Steps for hypothesis testing • Hypothesis testing with analysis of variance (ANOVA) • Interpreting excel output of hypothesis tests • Constructing brief, complete summary statements • Review for Exam 3

  7. Homework

  8. Homework

  9. Homework

  10. Type of major in school 4 (accounting, finance, hr, marketing) Grade Point Average Homework 0.05 2.83 3.02 3.24 3.37

  11. 0.3937 0.1119 If observed F is bigger than critical F:Reject null & Significant! If observed F is bigger than critical F:Reject null & Significant! 0.3937 / 0.1119 = 3.517 Homework 3.517 3.009 If p value is less than 0.05:Reject null & Significant! 3 24 0.03 4-1=3 # groups - 1 # scores - number of groups 28 - 4=24 # scores - 1 28 - 1=27

  12. Yes Homework = 3.517; p < 0.05 F (3, 24) The GPA for four majors was compared. The average GPA was 2.83 for accounting, 3.02 for finance, 3.24 for HR, and 3.37 for marketing. An ANOVA was conducted and there is a significant difference in GPA for these four groups (F(3,24) = 3.52; p < 0.05).

  13. Average for each group(We REALLY care about this one) Number of observations in each group Just add up all scores (we don’t really care about this one)

  14. Number of groups minus one(k – 1)  4-1=3 “SS” = “Sum of Squares”- will be given for exams Number of people minus number of groups (n – k)  28-4=24

  15. SS between df between SS within df within MS between MS within

  16. Type of executive 3 (banking, retail, insurance) Hours spent at computer 0.05 10.8 8 8.4

  17. 11.46 2 If observed F is bigger than critical F:Reject null & Significant! If observed F is bigger than critical F:Reject null & Significant! 11.46 / 2 = 5.733 5.733 3.88 If p value is less than 0.05:Reject null & Significant! 2 12 0.0179

  18. Yes p < 0.05 F (2, 12) = 5.73; The number of hours spent at the computer was compared for three types of executives. The average hours spent was 10.8 for banking executives, 8 for retail executives, and 8.4 for insurance executives. An ANOVA was conducted and we found a significant difference in the average number of hours spent at the computer for these three groups , (F(2,12) = 5.73; p < 0.05).

  19. Average for each group(We REALLY care about this one) Number of observations in each group Just add up all scores (we don’t really care about this one)

  20. Number of groups minus one(k – 1)  3-1=2 “SS” = “Sum of Squares”- will be given for exams Number of people minus number of groups (n – k)  15-3=12

  21. SS between df between SS within df within MS between MS within

  22. Five steps to hypothesis testing Step 1: Identify the research problem (hypothesis) Describe the null and alternative hypotheses Step 2: Decision rule • Alpha level? (α= .05 or .01)? Still, difference between means • Critical statistic (e.g. z or t or F or r) value? Step 3: Calculations MSBetween F = MSWithin Still, variabilityof curve(s) Step 4: Make decision whether or not to reject null hypothesis If observed t (or F) is bigger then critical t (or F) then reject null Step 5: Conclusion - tie findings back in to research problem

  23. Be sure to turn off any recording devices as these questions may not be distributed Review for Exam 3

  24. Thank you! See you next time!!