Associate Degree Programs
Vocational School of Technical Sciences
Computer Programming
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Statistics and Probability

Course CodeSemester Course Name LE/RC/LA Course Type Language of Instruction ECTS
TBP3916 3 Statistics and Probability 2/1/0 CC Türkçe 3
Course Goals
It is aimed to explain the definition of statistics to the student correctly, to teach the basic statistical concepts, to show the student how statistical applications and probability calculations in our daily life are useful and how important they are.
Prerequisite(s) Basic math knowledge
Corequisite(s) -
Special Requisite(s) -
Instructor(s) Assist. Prof. Dr. Yeliz Sevimli Saitoğlu
Course Assistant(s) -
Schedule Thursday; 13:30-16:30 -Ataköy Campus, 3C - 11-13-15
Office Hour(s) Monday; 11:00-12:00-İncirli Campus Office No: 2A05
Teaching Methods and Techniques Giving theoretical information about the courses
The applications on the computer
The problem solving with students on board and the computer by SPSS package program
SPSS end excel analysis done with the help of over the actual data  from  www.tuik.gov.tr 
Principle Sources

Serper Özer, Uygulamalı İstatistik I, Ezgi Kitabevi, Bursa
Akın Fahamet, Sosyal Bilimlerde İstatistik, 2002, ISBN 975-7338-91-5, Ekin Kitabevi, Bursa

Other Sources

Dündar Durmuş, Çağlar Nazan,  İstatistik(Temel Bilgiler, Yöntemler ve Uygulamalar), 2008, ISBN 978-975-353-351-5, Der Yayınevi, İstanbul 

Course Schedules
Week Contents Learning Methods
1. Week Basic Definition and Concepts Oral presentation
2. Week processing of data (Classification and Grouping) Oral presentation
3. Week Statistical tables and graphics, series Oral presentation
4. Week Time Series-Location Series-Frequency (Division) Series Oral presentation
5. Week Averages: Analytical Averages Oral presentation
6. Week Averages: Non-analytical Averages Oral presentation
7. Week Measures of Variability (Standard Deviation-Variance-Coefficient of Variation) Oral presentation
8. Week Midterm exam exam
9. Week Sampling Methods Oral presentation
10. Week Indices (Location and Time Indices) Oral presentation
11. Week Indices (Fixed and Variable Based Indices) Oral presentation
12. Week Compound Indices Oral presentation
13. Week Probability Theory Oral presentation
14. Week Probability Theory Oral presentation
15. Week Probability Theory Oral presentation
16. Week Simple Linear Regression and Correlation Analysis Oral presentation
17. Week Final exam exam
Assessments
Evaluation tools Quantity Weight(%)
Midterm(s) 1 25
Final Exam 1 75


Program Outcomes
PO-1Effectively identifying collecting and evaluating the data required for the Computer Programming field and using theoretical knowledge for creating applications.
PO-2Being equipped with basics of computer science.
PO-3Possessing the knowledge of all necessary software and equipment in the profession.
PO-4Emphasizing team work, contributing to the group and operating with team chemistry.
PO-5Effectively expressing and sharing the completed work with project group and teammates.
PO-6Objectively evaluating the performance of employees under his/her supervision and providing objective information to the management.
PO-7Demonstrating problem solving skills and the education he/she obtained at the program.
PO-8Possessing the computer programming knowledge built on skills, information and competencies provided by secondary education and supperted by higher education course materials, and demonstrating the understanding of concepts in the field of computer programming.
PO-9Acquiring the analytical thinking skills required in the field of computer programming, and creating and running programs in accordance with this analytical perspective.
PO-10Complying with ethical values of the field of Computer Programming and carrying social responsibility.
PO-11Developing sufficent foreign language skills to conduct the work and follow the global developments at the best level.
PO-12Empasizing communication and using Turkish accurately in this communication.
PO-13Ensuring the security, environment and health awareness at personal level and among his/her employees.
PO-14Following technological innovations in software and hardware after graduation and sustaining continuous personal development.
PO-15Claiming responsibility at his/her workplace, organizing work flow with employees and operating according to high quality work standards.
Learning Outcomes
LO-1To teach the purpose of statistical methodology
LO-2understanding the basic concepts and subjects of statistics and probability science
LO-3To teach how to interpret numerical indicators (statistical outputs)
LO-4To teach how to summarize all kinds of data with tables and graphs
LO-5To be able to educate students who will understand how important statistics are firstly in terms of science, and then in terms of state administration and business life.
Course Assessment Matrix:
Program Outcomes - Learning Outcomes Matrix
 PO 1PO 2PO 3PO 4PO 5PO 6PO 7PO 8PO 9PO 10PO 11PO 12PO 13PO 14PO 15
LO 1
LO 2
LO 3
LO 4
LO 5