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Information
| Code | ISB312 |
| Name | Analysis of Variance and Experimental Design |
| Term | 2022-2023 Academic Year |
| Semester | 6. Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 5 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. GÜLESEN ÜSTÜNDAĞ ŞİRAY |
| Course Instructor |
Prof. Dr. GÜLESEN ÜSTÜNDAĞ ŞİRAY
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
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.
Course Content
The content of this course is one-way Anova, binary and multiple comparisons, two-way Anova, incomplete randomized block designs, designs of Latin square, Greko-Latin square, Youden square, Anova for fixed, random and mixed effects designs, nested design, factorial designs.
Course Precondition
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Resources
1. Semra Oral Erbaş, Hülya Olmuş, Ezgi Nazman. Araştırmacılar İçin SPSS Uygulamalı İstatistiksel Deney Tasarımı. Gazi Kitabevi 2. Birdal Şenoğlu, Şükrü Acıtaş. İstatistiksel Deney Tasarımı-Sabit Etkili Modeller, Nobel Akademik Yayıncılık 3. Charles R. Hicks, Çevirmenler: Zehra Muluk, Öniz Toktamış, Ergun Karaağaoğlu, Serdar Kurt. Deney Düzenlemede İstatistiksel Yöntemler . Gazi Kitabevi
Notes
Lecture Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Explain the basic concepts of Anova and cause of used Anova. |
| LO02 | Analyze the one-way and two way Anovas. |
| LO03 | Check the assumptions necessary for the analysis of variance model. |
| LO04 | Make estimation for unknown parameters in the analysis of variance model. |
| LO05 | Generate the expected mean square error according to the fixed effect and random effect. |
| LO06 | Apply confidence intervals. |
| LO07 | Hypothesis tests about the parameters . |
| LO08 | Determine the sources of differences (which experiment or experiments) in case of rejection of the null hypothesis. |
| LO09 | Performs Anova by using SPSS and Minitab package programs. |
| LO10 | Analyze the incomplete randomized block designs, Latin square, Greko-Latin square and Youden square designs. |
| LO11 | Make the Anova for fixed, random and mixed effects designs. |
| LO12 | Construct the nested and factorial designs. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics | 4 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Emphasize the importance of Statistics in life | 4 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Define basic principles and concepts in the field of Law and Economics | |
| PLO04 | Bilgi - Kuramsal, Olgusal | Produce numeric and statistical solutions in order to overcome the problems | 4 |
| PLO05 | Bilgi - Kuramsal, Olgusal | Use proper methods and techniques to gather and/or to arrange the data | 5 |
| PLO06 | Bilgi - Kuramsal, Olgusal | Utilize computer systems and softwares | 4 |
| PLO07 | Bilgi - Kuramsal, Olgusal | Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events | 5 |
| PLO08 | Bilgi - Kuramsal, Olgusal | Apply the statistical analyze methods | 5 |
| PLO09 | Bilgi - Kuramsal, Olgusal | Make statistical inference(estimation, hypothesis tests etc.) | 5 |
| PLO10 | Bilgi - Kuramsal, Olgusal | Generate solutions for the problems in other disciplines by using statistical techniques | 5 |
| PLO11 | Bilgi - Kuramsal, Olgusal | Discover the visual, database and web programming techniques and posses the ability of writing programme | |
| PLO12 | Bilgi - Kuramsal, Olgusal | Construct a model and analyze it by using statistical packages | 4 |
| PLO13 | Beceriler - Bilişsel, Uygulamalı | Distinguish the difference between the statistical methods | 5 |
| PLO14 | Beceriler - Bilişsel, Uygulamalı | Be aware of the interaction between the disciplines related to statistics | 5 |
| PLO15 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Make oral and visual presentation for the results of statistical methods | |
| PLO16 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Have capability on effective and productive work in a group and individually | |
| PLO17 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | 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 | |
| PLO18 | Yetkinlikler - Öğrenme Yetkinliği | Develop scientific and ethical values in the fields of statistics-and scientific data collection |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Basic concepts of analysis of variance, construction of one-way Anova and checking the model assumptions | Source reading | Öğretim Yöntemleri: Anlatım, Problem Çözme, Soru-Cevap, Tartışma |
| 2 | Estimation of parameters and generation of the confidence intervals | Source reading | Öğretim Yöntemleri: Anlatım, Problem Çözme, Örnek Olay |
| 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 | Öğretim Yöntemleri: Anlatım, Problem Çözme, Soru-Cevap |
| 4 | Binary and multiple comparisons | Source reading | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 5 | Examples of Anova with SPSS and Minitab package program | Source reading | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 6 | Construction of two-way Anova (case 1), estimation of parameters, division of the sum of squares, construction of the Anova table | Source reading | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 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 | Öğretim Yöntemleri: Anlatım, Problem Çözme, Soru-Cevap |
| 8 | Mid-Term Exam | Review the topics discussed in the lecture notes and sources | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Incomplete randomized block designs. | Source reading | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 10 | Latin square, Greko Latin Square and Youden Square designs, estimation of parameters, division of the sum of squares, construction of the Anova table | Source reading | Öğretim Yöntemleri: Anlatım, Problem Çözme, Tartışma |
| 11 | Fixed, random and mixed effects designs, obtaining the expected mean square errors | Source reading | Öğretim Yöntemleri: Anlatım, Problem Çözme, Tartışma |
| 12 | Nested design, two and there step nested designs | Source reading | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 13 | l step nested design,obtaining the expected mean square errors, examples with SPSS and Minitab package program | Source reading | Öğretim Yöntemleri: Anlatım, Problem Çözme, Alıştırma ve Uygulama |
| 14 | Factorial designs | Source reading | Öğretim Yöntemleri: Anlatım, Problem Çözme, Alıştırma ve Uygulama |
| 15 | Factorial design, examples with SPSS and Minitab package program | Source reading | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 16 | Term Exams | Review the topics discussed in the lecture notes and sources | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Term Exams | Review the topics discussed in the lecture notes and sources | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 3 | 42 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 12 | 12 |
| Final Exam | 1 | 18 | 18 |
| Total Workload (Hour) | 114 | ||
| Total Workload / 25 (h) | 4,56 | ||
| ECTS | 5 ECTS | ||