GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
GENERAL STATISTICS/5391324
Course Title: GENERAL STATISTICS
Credits 3 ECTS 7.5
Semester 0 Compulsory/Elective Elective
COURSE INFO
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- NAME OF LECTURER(S)
  Asst. Prof. Dr. BENİAN TEKİNDAL
 -- WEB SITE(S) OF LECTURER(S)
  http://websitem.gazi.edu.tr/site/benian
 -- EMAIL(S) OF LECTURER(S)
  benian@gazi.edu.tr
 -- LEARNING OUTCOMES OF THE COURSE UNIT
General Statistical Issues
Relations with other disciplines of statistics
Introductory and representative values
Hypothesis Testing and Applications
Some branches of science related to the importance and application of statistical distributions




 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face
 -- PREREQUISITES AND CO-REQUISITES
  There is no prerequisite or co-requisite for this course.
 -- RECOMMENDED OPTIONAL PROGRAMME COMPONENTS
  There is no recommended optional programme component for this course.
 --COURSE CONTENT
1. Week  The concept of statistics, statistical meaning of the word
2. Week  The definition and scope of statistics, law of large numbers
3. Week  Interest in statistics and other sciences, tables and graphs
4. Week  The frequency distribution table, introductory statistics
5. Week  Sample space, probability concept
6. Week  Statistical distributions, sampling distributions
7. Week  Hypothesis Controls, Distribution of z and z Controls
8. Week  Distribution of t and t Controls
9. Week  Confidence Intervals
10. Week  Correlation and Regression Analysis
11. Week  Trend Analysis
12. Week  Index numbers
13. Week  F Distribution and Variance Analysis Technique
14. Week  Chi-Square Controls
15. Week  
16. Week  
 -- RECOMMENDED OR REQUIRED READING
  - Prof. Dr. Burhan ÇİL Statistics - Prof. Dr. Tahsin KESİCİ Prof. Dr. Zahide KOCABAŞ Biostatistics -Prof. Dr. Orhan DÜZGÜNEŞ Prof. Dr. Tahsin KESİCİ
 -- PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
  Lecture, Question & Answer, Demonstration, Drill - Practise
 -- WORK PLACEMENT(S)
  Not Applicable
 -- ASSESSMENT METHODS AND CRITERIA
 
Quantity
Percentage
 Mid-terms
1
40
 Assignment
1
10
 Exercises
0
0
 Projects
0
0
 Practice
0
0
 Quiz
0
0
 Contribution of In-term Studies to Overall Grade  
40
 Contribution of Final Examination to Overall Grade  
60
 -- WORKLOAD
 Efficiency  Total Week Count  Weekly Duration (in hour)  Total Workload in Semester
 Theoretical Study Hours of Course Per Week
15
3
45
 Practising Hours of Course Per Week
0
 Reading
15
3
45
 Searching in Internet and Library
15
3
45
 Designing and Applying Materials
15
3
45
 Preparing Reports
0
 Preparing Presentation
0
 Presentation
0
 Mid-Term and Studying for Mid-Term
0
 Final and Studying for Final
0
 Other
0
 TOTAL WORKLOAD: 
180
 TOTAL WORKLOAD / 25: 
7.2
 ECTS: 
7.5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1Improves and deepens the field knowledge at an expert level based on undergraduate proficiency.X
2Comprehends the interactions between the computer education and other related disciplines.X
3Uses expert level theoretical and practical knowledge acquired in the computer education field.X
4Creates new knowledge by integrating the computer education knowledge and the knowledge from related disciplines.X
5Defines a problem in the computer education field.X
6Analyses the problems in the computer education field by using scientific research methods.X
7Proposes solutions to the problems in the computer education field.X
8Solves problems in the computer education field.X
9Evaluates the results within perspectives of quality processes.X
10Develops new approaches and methods by taking responsibility in complex situations in the application stages.X