At the end of this course, the students; 1) Understand the types of questions that the statistical method addresses; 2) Apply the method to other examples and situations; 3) Implement the method using software (e.g., SPSS) 4) Interpret the results in a way that addresses the question of interest; 5) Communicate the purposes of the analyses, the findings from the analysis, and the implicationsof those findings.
MODE OF DELIVERY
Face to face
PRE-REQUISITES OF THE COURSE
No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
None
COURSE DEFINITION
Basic Concepts in Statistics, Variance and Covariance analysis, Multiple regression analysis, Exploratory and Confirmatory Factor Analysis, Path Analysis, AMOS and LISREL aplications, Power, Effect Size, the interaction among power, effect size, and sample size.
COURSE CONTENTS
WEEK
TOPICS
1st Week
Overview of Descriptive Statistics
2nd Week
Sampling Distribution in Statistics, Data Creation, Data Cleaning, Types of Data, Data Screening
3rd Week
Overview of One Sample Tests
4th Week
Overview of Two Sample Cases, Determining Sample Size, Power and Effect Size
5th Week
ANOVA Models (One-way)
6th Week
ANOVA Models (Two-way, Three-way)
7th Week
Repeated ANOVA (One-Way)
8th Week
Repeated ANOVA (Two-Way)
9th Week
Covariance Analysis in ANOVA Models
10th Week
MANOVA Models
11th Week
Canonical Correlation
12th Week
Multivariate Regression Analysis
13th Week
Multivariate Regression Analysis
14th Week
Discriminant Analysis, Factor Analysis
15th Week
RECOMENDED OR REQUIRED READING
Pituch, K.A. & Stevens, J.P. (2016). Applied Multivariate Statistics for the Social Sciences: Analyses with SAS and IBM?s SPSS, 6th Edition. Routledge, Taylor & Francis. New York. Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics. Boston: Pearson/Allyn & Bacon.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
Lecture,Problem Solving,Practice
ASSESSMENT METHODS AND CRITERIA
Quantity
Percentage(%)
Mid-term
1
40
Total(%)
40
Contribution of In-term Studies to Overall Grade(%)
40
Contribution of Final Examination to Overall Grade(%)
60
Total(%)
100
ECTS WORKLOAD
Activities
Number
Hours
Workload
Midterm exam
1
12
12
Preparation for Quiz
Individual or group work
14
10
140
Preparation for Final exam
1
30
30
Course hours
14
1
14
Preparation for Midterm exam
1
20
20
Laboratory (including preparation)
14
2
28
Final exam
1
15
15
Homework
10
4
40
Total Workload
299
Total Workload / 30
9,96
ECTS Credits of the Course
10
LANGUAGE OF INSTRUCTION
Turkish
WORK PLACEMENT(S)
No
KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)
