Course Information


Course Information
Course Title Code Semester L+U Hour Credits ECTS
STATISTICS ABE0000007 1 + 0 1.0 3.0

Prerequisites None

Language of Instruction
Course Level Graduate Degree
Course Type Compulsory
Mode of delivery
Course Coordinator
Instructors
Assistants
Goals The aim is for students to learn the fundamental concepts of statistics, gain knowledge and skills about statistical methods used to analyze data, and acquire proficiency in planning, analyzing, and interpreting research.
Course Content Statistical concepts, fundamental concepts, data types and measurement levels, frequency tables and graphs, the concept of probability, some continuous and discrete probability distributions, sampling distributions, hypothesis tests, point and interval estimation, regression and correlation, one-way and two-way ANOVA, categorical data, chi-square tests and association coefficients, applications using a well-known statistical program.
Learning Outcomes 1) Recognises data and variable types, processes data before analysis
2) Summarises and interprets the data with tables and graphs
3) Decides on the statistical methods to be used according to the data structure
4) Use statistical methods in programming language and interpret the results
5) Gain experience working with real data from different disciplines
6) Establishes relationships between theoretical and practical knowledge
7) Gains the competence of recognising, modelling and interpreting the results of real life problems involving uncertainty

Weekly Topics (Content)
Week Topics Teaching and Learning Methods and Techniques Study Materials
1. Week Statistical concepts, fundamental concepts, data types and measurement levels, Frequency Tables and Graphs Lecture; Question Answer; Problem Solving; Discussion; Case Study
Colloquium; Large Group Discussion
Problem Based Learning; Brain Based Learning 		Homework Presentation (Including Preparation Time) Report (Including Preparation and presentation Time) Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice) Seminar
2. Week Measures of Central Tendency and Dispersion Lecture; Question Answer; Problem Solving; Case Study
Brainstorming; Colloquium
Problem Based Learning 		Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
3. Week Probability and Probability Theory Lecture; Question Answer; Problem Solving; Discussion
Brainstorming; Colloquium
Problem Based Learning 		Homework Presentation (Including Preparation Time) Report (Including Preparation and presentation Time) Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
4. Week Random Variables and Their Distributions Lecture; Discussion; Case Study
Brainstorming; Colloquium
Problem Based Learning 		Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
5. Week Some Discrete Probability Distributions Lecture; Discussion; Case Study
Brainstorming; Colloquium
Problem Based Learning 		Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
6. Week Some Continuous Probability Distributions Lecture; Discussion; Case Study
Brainstorming; Colloquium
Problem Based Learning 		Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
7. Week Sampling and Sampling Distributions Lecture; Problem Solving; Discussion
Brainstorming; Colloquium
Problem Based Learning 		Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
8. Week Hypothesis Testing-1 (Hypothesis, Test Statistics, Error Types, Hypothesis Tests Related to Population Mean) Lecture; Discussion; Case Study
Brainstorming; Colloquium
Problem Based Learning 		Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
9. Week Hypothesis Testing-2 (Hypothesis Tests Related to Population Proportion and Population Variance) Lecture; Problem Solving; Discussion
Brainstorming; Colloquium
Problem Based Learning 		Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
10. Week Point and Interval Estimation (Interval Estimation for Population Mean, Proportion, and Variance) Lecture; Discussion; Case Study
Brainstorming; Colloquium
Problem Based Learning 		Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
11. Week Simple Linear Regression and Correlation Lecture; Discussion; Case Study
Brainstorming; Colloquium
Problem Based Learning 		Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
12. Week One-Way and Two-Way Analysis of Variance (ANOVA) Lecture; Discussion; Case Study
Brainstorming; Colloquium
Problem Based Learning 		Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
13. Week Categorical Data, Chi-Square Tests, and Measures of Association Lecture; Discussion; Case Study
Brainstorming; Colloquium
Problem Based Learning 		Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
14. Week Applications and Interpretations of Statistical Methods in a Programming Language Environment Lecture; Question Answer; Problem Solving; Discussion; Case Study
Brainstorming; Colloquium
Problem Based Learning 		Homework Presentation (Including Preparation Time) Report (Including Preparation and presentation Time) Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)

Sources Used in This Course
Recommended Sources
Alpar,R. 2016, Uygulamalı İstatistik ve Geçerlilik-Güvenirlilik,Detay Yayıncılık,Ankara.
Johnson R.A. ve Bhattacharyya G.K. Statistics.(Principles and Methods) John Wiley and Sons, Inc. U.S.A.,2006.
Moore, D. S., McCabe, G. P. Introduction to the Practice of Statistics, W. H. Freeman Company, Newyork,2003.
Oral,E.S., 2016, Olasılık ve İstatistik,Gazi Kitapevi,5.baskı,Ankara
Wackerly, D.D.,Mendenhall,W.,Scheaffer,R.L.,(2008). Mathematical Statistcs with Applications,7.Edition, Thomson Learning.
Walpole,R.E., Myers, R.H., Myers, S.L.,Ye,K. (2016). Mühendisler ve Fen Bilimciler için Olasılık ve İstatistik, Palme Yayıncılık,9. Baskı. Ankara.
Wilcox, RR., Understanding and Applying Basic Statistical Methods Using R, 2017 John Wiley & Sons.Kloke,J., McKean, JW., Nonparametric Statistical Methods Using R., 2015 by Taylor & Francis Group, LLC

ECTS credits and course workload
Event Quantity Duration (Hour) Total Workload (Hour)
Course Duration (Total weeks*Hours per week) 14 1
Work Hour outside Classroom (Preparation, strengthening) 14 1
Midterm Exam 1 1
Time to prepare for Midterm Exam 14 2
Final Exam 1 1
Time to prepare for Final Exam 14 2
Total Workload
Total Workload / 30 (s)
ECTS Credit of the Course
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Course Information
  • Course Information
  • Weekly Topics (Content)
  • Sources Used in This Course
  • ECTS credits and course workload