Information Package
baskent.edu.tr

Master's of Computer and Instructional Technologies Education with Thesis

BÖTE612

ADVANCED STATISTICS

Course Code
BÖTE612
Semester
-
Theory+Practice
2 + 2
ECTS
5
Course TypeElective Course
Course LevelMaster's Degree With Thesis
Year of Study-
Semester-
ECTS5
Name of Lecturer(s)
Learning Outcomes

At the end of this course, the students;

  1. Will be able to explain advanced statistical methods,
  2. will be able to use univariate and multivariate statistical methods,
  3. will be able to make statistical applications in the appropriate package program,
  4. Will be able to determine and apply the appropriate statistical analysis techniques according to the research purpose and interpret the results of these analyzes correctly,
  5. Will be able to know which tests will be used in which situations, will be able to interpret the results of the analysis by making calculations about them.
Mode of DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme ComponentsBÖTE611
Course DescriptionApplication of advanced statistical methods required for educational research. Conducting statistical analysis such as correlation, variance, covariance. Understanding and conducting confirmation and exploratory factor analyses, and structural equation modeling
Course Contents
WEEK TOPICS
1st Week Basic concepts
2nd Week Regression Analysis
3rd Week Multiple Frequency Analysis
4th Week Covariance Analysis (Ancova)
5th Week Multivariate Analysis of Variance (Manova)
6th Week Logistic Regression
7th Week Spss-Application
8th Week Midterm
9th Week Cluster Analysis
10th Week Discriminant Analysis
11th Week Exploratory Factor Analysis
12th Week Structural Equation Models
13th Week Confirmatory Factor Analysis
14th Week Spss-Application
Recommended or Required Reading1) Arıcı,Hüsnü. (1984) İstatistik Yöntemler ve Uygulamalar. Ankara: Meteksan Matbaacılık

2) Büyüköztürk, (2006). Soysal Bilimler İçin Veri analizi El Kitabı. Ankara: Pegem Yayınları.

3) Büyüköztürk, Ş., Çokluk, Ö. ve Köklü, N. (2011). Sosyal Bilimler İçin İstatistik (7.baskı). Türkiye. Pegem.

4) Cula, S., & Muluk, Z. (2006). Temel istatistik yöntemleri. Başkent Üniversitesi.

5) Freund, J. E., & Perles, B. M. (2007). Modern elementary statistics. Prentice Hall.

6) Gravetter F. & Wallnau L., B., (1985)Statistics for the Behavivioral Sciences. West Publishing co. Minnesota, USA.

7) Hinkle, D.E.,Wiersma, W., ve Jurs, S.G. (1988) Applied Statistics for the Behavioral Sciences. Boston: Houghton Mifflin Company

8) Tavşancıl E. (2006). Tutumların Ölçülmesi ve SPSS ile Veri Analizi, Nobel Yayın Dağıtım, 3. Baskı.
Planned Learning Activities and Teaching Methods
  • Lecture
  • Discussion
  • Problem Solving
  • Questions/Answers
  • Project
Assessment Methods and Criteria
Quantity Percentage (%)
Mid-term 1 30
Assignment 2 20
Total(%) 50
Contribution of In-term Studies to Overall Grade(%) 50
Contribution of Final Examination to Overall Grade(%) 50
Total(%) 100
ECTS Allocated Based on Student Workload
Activities Quantity Duration (Hour) Total Workload (Hour)
Midterm exam 1 3 3
Preparation for Quiz
Individual or group work 14 3 42
Preparation for Final exam 1 25 25
Course hours 14 4 56
Preparation for Midterm exam 1 15 15
Laboratory (including preparation)
Final exam 1 3 3
Homework 2 4 8
Total Work Load152
Total Work Load / 30 (h)5.06
ECTS Credit of the Course5
Language of InstructionTurkish
Work Placement(s)No

Programme Qualifications / Learning Outcomes

LO1 LO2 LO3 LO4 LO5
K1 X X
K2 X
K3
K4
K5 X X X X X
K6 X X X X
K7 X X X X X
K8 X
K9 X X X X
K10
K11 X
K12
K13 X X X
K14
K15 X
K16
K17
K18