GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
Data Analysis in Quantitative Research/4310030
Course Title: Data Analysis in Quantitative Research
Credits 3 ECTS 7
Course Semester 1 Type of The Course Elective
COURSE INFORMATION
 -- (CATALOG CONTENT)
 -- (TEXTBOOK)
 -- (SUPPLEMENTARY TEXTBOOK)
 -- (PREREQUISITES AND CO-REQUISITES)
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- COURSE OBJECTIVES
 -- COURSE LEARNING OUTCOMES
Explains basic concepts of statistics.
Organizes the data with descriptive statistics techniques and produces descriptive statistics table.
Chooses the appropriate estimate of central tendency in summarizing a given data set.
Explains the statistical terminology and concepts used in a research paper.
Chooses and applies an appropriate inferential statistical technique for a given data set.
Applies the steps of hypothesis testing.
Explains that the inferential statistics techniques are based on probability concept.
Uses software (SPSS) in conducting statistical analyses.
Describes the effect size and statistical power concepts and interprets the calculated values for effect size and power.
 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face
 --WEEKLY SCHEDULE
1. Week  Quantitative research designs, internal and external validity, differences between quantitative and qualitative research designs Basic definitions
2. Week  Organization of data (frequency distribution), central tendency
3. Week  Variability (standard deviation, variance), maximum and minimum scores, skewness and kurtosis coefficients, SPSS applications in descriptive statisti
4. Week  Probability, z-scores, normal distribution, distribution of sample means
5. Week  Inferential statistics and hypothesis testing, single sample t-test
6. Week  Independent samples t-test and SPSS applications
7. Week  Related samples t-test and SPSS applications
8. Week  Mid-term
9. Week  One–way ANOVA and SPSS applications
10. Week  Two-way ANOVA and SPSS applications
11. Week  Repeated ANOVA and SPSS applications, nonparametric tests
12. Week  Correlation and Simple linear regression and SPSS applications
13. Week  Multiple regression and SPSS applications
14. Week  ANCOVA and SPSS applications
15. Week  
16. Week  
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
1
60
 Assignment
9
40
 Application
0
0
 Projects
0
0
 Practice
0
0
 Quiz
0
0
 Percent of In-term Studies  
40
 Percentage of Final Exam to Total Score  
60
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
14
3
42
 Weekly Tutorial Hours
0
 Reading Tasks
14
4
56
 Searching in Internet and Library
0
 Material Design and Implementation
12
2
24
 Report Preparing
1
5
5
 Preparing a Presentation
1
4
4
 Presentation
1
1
1
 Midterm Exam and Preperation for Midterm Exam
1
20
20
 Final Exam and Preperation for Final Exam
1
25
25
 Other (should be emphasized)
0
 TOTAL WORKLOAD: 
177
 TOTAL WORKLOAD / 25: 
7.08
 Course Credit (ECTS): 
7
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1X
2X
3X
4X
5X
6X
7X
8X
9X
10X
11X
12X
13X
14X
 -- NAME OF LECTURER(S)
   (Prof.Dr. Nejla Yürük )
 -- WEB SITE(S) OF LECTURER(S)
   (www.websitem.gazi.edu.tr/site/nejlayuruk)
 -- EMAIL(S) OF LECTURER(S)
   (nejlayuruk@gazi.edu.tr)