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•           Information on Degree Programmes

COURSE INFORMATON
Course Title Code Semester L+P Hour Credits ECTS
Analysis of Variance and Experimental Design * ISB   312 6 3 3 5

 Prerequisites and co-requisites Yok Recommended Optional Programme Components None

Language of Instruction Turkish
Course Level First Cycle Programmes (Bachelor's Degree)
Course Type
Course Coordinator Assoc.Prof.Dr. Gülesen ÜSTÜNDAĞ ŞİRAY
Instructors
 Doç.Dr. GÜLESEN ÜSTÜNDAĞ ŞİRAY 1. Öğretim Grup:A Doç.Dr. GÜLESEN ÜSTÜNDAĞ ŞİRAY 2. Öğretim Grup:A

Assistants
Goals
To construct the necessary theoretical background in undergraduate teaching, to analyze the data that can be faced at the public and private sectors, to gain the knowledge, skills, and practicality for interpreting the results of the analysis.
Content
One-way Anova, Binary and multiple comparisons, Two-way Anova, Designs of Latin Square and Greko-Latin square, Nested design, Factorial designs

Learning Outcomes
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Course's Contribution To Program
NoProgram Learning OutcomesContribution
12345
1
Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics
X
2
Emphasize the importance of Statistics in life
X
3
Define basic principles and concepts in the field of Law and Economics
4
Produce numeric and statistical solutions in order to overcome the problems
X
5
Use proper methods and techniques to gather and/or to arrange the data
X
6
Utilize computer systems and softwares
X
7
Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events
X
8
Apply the statistical analyze methods
X
9
Make statistical inference(estimation, hypothesis tests etc.)
X
10
Generate solutions for the problems in other disciplines by using statistical techniques
X
11
Discover the visual, database and web programming techniques and posses the ability of writing programme
12
Construct a model and analyze it by using statistical packages
X
13
Distinguish the difference between the statistical methods
X
14
Be aware of the interaction between the disciplines related to statistics
X
15
Make oral and visual presentation for the results of statistical methods
X
16
Have capability on effective and productive work in a group and individually
X
17
Professional development in accordance with their interests and abilities, as well as the scientific, cultural, artistic and social fields, constantly improve themselves by identifying training needs
18
Develop scientific and ethical values in the fields of statistics-and scientific data collection
X

Course Content
WeekTopicsStudy Materials _ocw_rs_drs_yontem
1 Basic concepts of analysis of variance, construction of one-way Anova and checking the model assumptions Source reading
2 Estimation of parameters and generation of the confidence intervals Source reading
3 Division of the basic sum of squares, construction of the Anova table, testing of the hypothesis, obtaining the expected mean square errors Source reading
4 Binary and multiple comparisons Source reading
5 Examples of Anova with SPSS and Minitab package program Source reading
6 Construction of two-way Anova (case 1), estimation of parameters, division of the sum of squares, construction of the Anova table Source reading
7 Construction of two-way Anova (cases 2 and 3), estimation of parameters, division of the sum of squares, construction of the Anova table Source reading
8 Mid-term exam Review the topics discussed in the lecture notes and sources
9 Obtaining the expected mean square errors for two way Anova, missing observations Source reading
10 Latin square design, estimation of parameters, division of the sum of squares, construction of the Anova table Source reading
11 Latin square design, estimation of parameters, division of the sum of squares, construction of the Anova table, obtaining the expected mean square errors Source reading
12 Nested design, two and there step nested designs Source reading
13 l step nested design,obtaining the expected mean square errors, examples with SPSS and Minitab package program Source reading
14 Factorial design Source reading
15 Factorial design, examples with SPSS and Minitab package program Source reading
16-17 Final exam Review the topics discussed in the lecture notes and sources

Recommended or Required Reading
Textbook