1. Course number and name

010913333-65 สถิติวิศวกรรม (Engineering Statistics)

2. Credits and contact hours

3(3-0-6)

3. Instructor’s or course coordinator’s name

Assoc.Prof. Dr.Krisada Asawarungsaengkul
Asst.Prof. Dr.Phattarasaya Tantiwattanakul

4. Text book, title, author, and year

1. Probability & Statistics for Engineers & Scientists, Ronald Walpole, Raymond Myers, Sharon Myers, Keying Ye, 9th Edition, Pearson, 2016.
2. Design and Analysis of Experiments, Douglas C. Montgomery, 8th Edition, John Wiley & Sons, Inc., 2012.
3. Applied Statistics and Probability for Engineers, Douglas C. Montgomery and George C. Runger, 7th Edition, John Wiley & Sons, Inc., 2020.

5. Specific course information

1. brief description of the content of the course (catalog description)
   Principles of design of experiment; analysis of variance; design of experiment for single factor; randomized complete block design; general full factorial experiment; two-level factorial experiment; single replicate of two-level factorial experiment; two-level factorial experiment with center points; response surface experiment; multiple regression analysis.
2. prerequisites or co-requisites
   040503011-65 Statistics for Engineers and Scientists
3. indicate whether a required, elective, or selected elective (as per Table 5-1) course in the program
   Required :

6. Specific goals for the course

1. specific outcomes of instruction (e.g. The student will be able to explain the significance of current research about a particular topic.)
   1. CLO1 Explain the principle of design of experiment (DOE).
   2. CLO2 Explain the data collection, how to define the factors and response variable, and select the appropriate DOE.
   3. CLO3 Calculate and conduct the analysis of variance (ANOVA); interpret and determine the significant factors; and formulate the regression model.
   4. CLO4 Perform the model adequacy checking for ANOVA and identify the error or noise of model.
   5. CLO5 Interpret the graphical plot and the regression model to make the conclusion and to determine the appropriate process parameters under constraints.
   6. CLO6 Utilize optimization approach to determine the appropriate process parameters.
   7. CLO7 Perform the multiple linear regression analysis and formulate the regression model.
2. explicitly indicate which of the student outcomes listed in Criterion 3 or any other outcomes are addressed by the course.

   ABET Student Outcome (SO) Listed in Criterion 3	Performance indicator
   SO1 an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics.	PI-1.1 Identify the problem and identify key issues/variables PI-1.2 Formulate an appropriate model of a system or process PI-1.3 Show solution procedure (or Solving methods)
   SO6 an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.	PI-6.1 Design an Experiment Plan (How to answer the Driving Question?) and Identify the factors and response variable PI-6.2 Acquire data on appropriate variables PI-6.3 Interpret experimental data and results with respect to appropriate theoretical models PI-6.4 Validate the model; Explain observed differences between model and experiment (bad model, bad measurements, noise, etc.) and draw conclusions

7. Brief list of topics to be covered

8. Course Assessment