Information Package
baskent.edu.tr

Master's of Computer and Instructional Technologies Education without Thesis (Distance Education)

BOTU611

STATISTICAL METHODS IN EDUCATION

Course Code
BOTU611
Semester
First Term (Fall)
Theory+Practice
2 + 2
ECTS
8
Course TypeCompulsory Course
Course LevelMaster's Degree Without Thesis
Year of Study1
SemesterFirst Term (Fall)
ECTS8
Name of Lecturer(s)
Learning Outcomes

At the end of this course, the students;

  1. Will be able to explain the basic concepts of statistics,
  2. will be able to organize and analyze the data set,
  3. Will be able to discuss the concepts of sample distribution and normal distribution,
  4. Will be able to calculate and interpret descriptive statistics and standard scores,
  5. Will be able to establish and test hypotheses suitable for the purpose / research question of the research,
  6. 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,
  7. Will be able to know which tests used in which situations, will be able to interpret the results of the analysis by making calculations about them.
Mode of DeliveryE-Learning
PrerequisitesNo
Recommended Optional Programme ComponentsNone
Course DescriptionThe introduction of basic statistical concepts and methods, conducting educational research and analysis necessary to carry out data collection, coding, sampling, data organizing, comparison, procedure and the teaching of statistical methods such as correlation
Course Contents
WEEK TOPICS
1st Week Introduction to Statistics
2nd Week Basic Concepts
3rd Week Sampling
4th Week Frequency Distributions
5th Week Goodness of Fit to Normal Distribution
6th Week Measures of Central Tendency
7th Week SPSS Application
8th Week Evaluation - Problem Solving
9th Week Inferential Statistics
10th Week Hypothesis Testing
11th Week T-test
12th Week Analysis of Variance
13th Week Correlation
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
  • Questions/Answers
  • Problem Solving
  • Project
Assessment Methods and Criteria
Quantity Percentage (%)
Assignment 4 20
Total(%) 20
Contribution of In-term Studies to Overall Grade(%) 20
Contribution of Final Examination to Overall Grade(%) 80
Total(%) 100
ECTS Allocated Based on Student Workload
Activities Quantity Duration (Hour) Total Workload (Hour)
Midterm exam
Preparation for Quiz
Individual or group work 14 8 112
Preparation for Final exam 1 35 35
Course hours 14 4 56
Preparation for Midterm exam
Laboratory (including preparation)
Final exam 1 3 3
Homework 4 8 32
Total Work Load238
Total Work Load / 30 (h)7.93
ECTS Credit of the Course8
Language of InstructionTurkish
Work Placement(s)No

Programme Qualifications / Learning Outcomes

LO1 LO2 LO3 LO4 LO5 LO6 LO7
K1 X X X X
K2 X
K3 X
K4 X
K5 X X
K6 X X X
K7 X X X X X X X
K8 X X X X X
K9 X X
K10 X
K11 X
K12
K13
K14 X X
K15
K16
K17 X
K18