DESIGN of EXPERIMENT

AIM

This course aims to teach the basic principles and methods of statistical experimental design.

CONTENT

This course contains; Review of Basic Statistical Concepts,Introduction to Design of Experiments,Comparing Multiple Means. Analysis of Variance (ANOVA),Single Factor Experiments & One-Way Analysis of Variance,One-Way Analysis of Variance. Simultaneous Confidence Intervals. Parameter Estimation.,Expected Mean Square (EMS) & Power Calculations,Special Case of Two Averages,Random Effects Model,Randomized Block Designs,Multifactor Designs,Two-Factor Experiments I,Two-Factor Experiments II,Mixed Effect Models,2k Multifactor Designs.

1. 1

   5.Use statistical package SPSS.

   Taught by: Case Study Method, Self Study Method, Lecture Method · Assessed by: Project Task

2. 2

   4.Evaluate random effects and mixed effects

   Taught by: Problem Solving Method, Case Study Method, Lecture Method · Assessed by: Traditional Written Exam

3. 3

   3.Analyze the results of the experiment with Analysis of Variance (Anova)

   Taught by: Problem Solving Method, Case Study Method, Lecture Method · Assessed by: Traditional Written Exam

4. 4

   1. Collect, analyze, interpret and present data

   Taught by: Case Study Method, Self Study Method, Question - Answer Technique, Lecture Method · Assessed by: Traditional Written Exam

5. 5

   2. Design Engineering Experiments

   Taught by: Case Study Method, Question - Answer Technique, Lecture Method · Assessed by: Traditional Written Exam

WEEKLY PLAN

1. WEEK 1

   Review of Basic Statistical Concepts

2. WEEK 2

   Introduction to Design of Experiments

3. WEEK 3

   Comparing Multiple Means. Analysis of Variance (ANOVA)

4. WEEK 4

   Single Factor Experiments & One-Way Analysis of Variance

5. WEEK 5

   One-Way Analysis of Variance. Simultaneous Confidence Intervals. Parameter Estimation.

6. WEEK 6

   Expected Mean Square (EMS) & Power Calculations

7. WEEK 7

   Special Case of Two Averages

8. WEEK 8

   Random Effects Model

9. WEEK 9

   Randomized Block Designs

10. WEEK 10

    Multifactor Designs

11. WEEK 11

    Two-Factor Experiments I

12. WEEK 12

    Two-Factor Experiments II

13. WEEK 13

    Mixed Effect Models

14. WEEK 14

    2k Multifactor Designs

ASSESSMENT

• Rate of Midterm Exam to Success30%
• Rate of Final Exam to Success70%

WORKLOAD

READING

• Design and Analysis of Experiments, 7th Ed. D. C. Montgomery, John Wiley & Sons, 2009.
• Probability and Statistics for Engineers and Scientists, 9th Ed. R. E. Walpole, R. H. Myers, S. L. Myers and K. Ye , Pearson Education 2012.

TEACHING STAFF

• Assoc.Prof. Melis Almula KARADAYICOORDINATOR
• Assoc.Prof. Melis Almula KARADAYI