At the end of this course, the students; 1) Define research methods. 2) Define data and data types. 3) Define data collection methods and use them. 4) Conduct data analysis using SPSS.
MODE OF DELIVERY
PRE-REQUISITES OF THE COURSE
No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
COURSE DEFINITION
Basic concepts, qualitative and quantitative methods, design of research and data collection methods, data analysis with SPSS, graphical data analysis, data distribution, data reliability, the analysis of cross-classified tables, mean statistics, hypothesis tests and correlation analysis.
COURSE CONTENTS
WEEK
TOPICS
1st Week
Basic concepts
2nd Week
Qualitative and quantitative methods
3rd Week
Design of research and data collection methods
4th Week
Design of research and data collection methods
5th Week
Data analysis with SPSS
6th Week
ata analysis with SPSS
7th Week
Graphical data analysis
8th Week
MIDTERM
9th Week
Data distribution, data reliability, the analysis of cross-classified tables
10th Week
Data distribution, data reliability, the analysis of cross-classified tables
11th Week
Mean statistics
12th Week
Hypothesis tests
13th Week
Correlation analysis
RECOMENDED OR REQUIRED READING
A. Field. Discovering statistics using SPSS. 3. Baskı, Sage publications, 2009. J. Pallant. SPSS Survival Manual, 2002.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
ASSESSMENT METHODS AND CRITERIA
ECTS WORKLOAD
Activities
Number
Hours
Workload
Midterm exam
1
2
2
Preparation for Quiz
0
0
0
Individual or group work
0
0
0
Preparation for Final exam
1
9
9
Course hours
14
3
42
Preparation for Midterm exam
1
5
5
Laboratory (including preparation)
0
0
0
Final exam
1
2
2
Homework
0
0
0
Total Workload
60
Total Workload / 30
2
ECTS Credits of the Course
2
LANGUAGE OF INSTRUCTION
WORK PLACEMENT(S)
No
KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)