STAT457 STATISTICAL DESIGN OF EXPERIMENTS

Course Code:2460457
METU Credit (Theoretical-Laboratory hours/week):4 (3.00 - 2.00)
ECTS Credit:6.0
Department:Statistics
Language of Instruction:English
Level of Study:Undergraduate
Course Coordinator:Prof.Dr. İNCİ BATMAZ
Offered Semester:Fall Semesters.

Course Objectives


Course Content

Strategies for Experimentation, Randomized Complete and Balanced Incomplete Block Designs, Latin Squares. General, Two-Level and Fractional Factorials. Blocking and Confounding in Two-Level Factorials. Introduction to Response Surface Methodology. Second-Order Experimental Designs. Nonnormal Responses. Unbalanced Data in Factorials. Split-Plot Designs, Nested Designs, Random Effect Models. Repeated Measures.


Course Learning Outcomes


Program Outcomes Matrix

Level of Contribution
#Program Outcomes0123
1Applying the knowledge of statistics, mathematics and computer to statistical problems and developing analytical solutions.✔
2Defining, modeling and solving real life problems that involve uncertainty, and interpreting results.✔
3To decide on the data collection technique, and apply it through experiment, observation, questionnaire or simulation.✔
4Analysing small and big volumes of data and interpreting results.✔
5Utilizing up-to-date techniques, computer hardware and software required for statistical applications; developing software programs and numerical solutions for specific problems when necessary.✔
6Taking part in intradisciplinary and interdisciplinary teamwork, using time efficiently, taking leadership responsibilities and being entrepreneurial.✔
7Taking responsibility in individual work and offering authentic solutions.✔
8Following contemporary developments and publications in statistical science, conducting research, being open to novelty and thinking critically.✔
9Efficiently communicating in Turkish and English to define and analyze statistical problems and to interpret the results.✔
10Having a professional and ethical sense of responsibility.✔
11Developing computational solutions to statistical problems that cannot be solved analytically.✔
12Having theoretical background and developing new theories in statistics, building relations between theoretical and practical knowledge.✔
13Serving the society with the expertise in the field.✔

0: No Contribution 1: Little Contribution 2: Partial Contribution 3: Full Contribution