GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
PROBABILITY AND STATISTICS II/İST- 292
Course Title: PROBABILITY AND STATISTICS II
Credits 3 ECTS 5
Semester 4 Compulsory/Elective Elective
COURSE INFO
 -- LANGUAGE OF INSTRUCTION
  TURKISH
 -- NAME OF LECTURER(S)
  Prof.Dr.Semra Erbaş
 -- WEB SITE(S) OF LECTURER(S)
  http://websitem.gazi.edu.tr/site/serbas
 -- EMAIL(S) OF LECTURER(S)
  serbas@gazi.edu.tr
 -- LEARNING OUTCOMES OF THE COURSE UNIT
Student learn probability concept and probability computation
Student learn probability distributions and examples of these distributions in daily life
Student learn how to plan and commutea research
Student learn what statistical methods,hypothesis tests and prediction are and how to use these
 -- 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 fort his course
 -- RECOMMENDED OPTIONAL PROGRAMME COMPONENTS
  There is no prerequisite or co-requisite fort his course
 --COURSE CONTENT
1. Week  Sampling,choosing sample,sampling error and sampling distributions
2. Week  Error types,hypothesis tests of one and two mass means
3. Week  hypothesis tests of one and two mass prpportions, hypothesis tests of one and two mass variances
4. Week  Prediction, prediction of one and two mass means
5. Week  prediction of one and two mass proportions,prediction of of one and two mass variances
6. Week  Goodness of fit tests, fitting to Binom,Poisson and normal distributions
7. Week  Independency test,homogeneity test,measurement of relations
8. Week  Mid-term exam
9. Week  Regression concept,linear regression, scatter plot
10. Week  Assumptions of least square method,confidence intervals and hypothesis tests
11. Week  Covariance,correlation
12. Week  One-way variance analysis,hypothesis tests for variances equation
13. Week  Multi-comparision
14. Week  Two-way variance analysis
15. Week  Random block design,latin square method,greko latin square method
16. Week  Final exam
 -- RECOMMENDED OR REQUIRED READING
  Oral Erbaş,S .Olasılık ve İstatistik.Gazi Kitabevi,2013
 -- PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
  Various statistical tables and lecture book,lecture notes
 -- WORK PLACEMENT(S)
  No
 -- ASSESSMENT METHODS AND CRITERIA
 
Quantity
Percentage
 Mid-terms
1
40
 Assignment
0
0
 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
10
3
30
 Practising Hours of Course Per Week
4
3
12
 Reading
0
0
0
 Searching in Internet and Library
2
2
4
 Designing and Applying Materials
1
2
2
 Preparing Reports
1
2
2
 Preparing Presentation
1
2
2
 Presentation
0
0
0
 Mid-Term and Studying for Mid-Term
3
7
21
 Final and Studying for Final
4
8
32
 Other
2
4
8
 TOTAL WORKLOAD: 
113
 TOTAL WORKLOAD / 25: 
4.52
 ECTS: 
5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1To train individuals who are contemporary, entrepreneur and have unique and aesthetic values, self-confidence and capable of independent decision-making.X
2To give good education in the program fields as algebra, geometry, applied mathematics, topology and analysis in order to be equipped with enough mathematics.X
3To teach mathematical thinking methods in order to improve the ability to express mathematics both orally and in writing.X
4To train individuals who are knowledgeable about the history of mathematics and the production of scientific knowledge and can follow developments in these disciplines.X
5To provide necessary equipments to take positions such areas as banking, finance, econometrics, and actuarial.X
6To acquire ability to solve problems encountered in real life by means of mathematical modeling using mathematical methods.X
7To provide ability to do necessary resource researches in the areas of mathematics and to use accessed information.X
8To give appropriate training in such areas as in computer programming and creating algorithms in order to take parts in developing IT sector.X
9To gain substructure to be able to study at graduate level.X
10To enable the student to gain the ability of relating mathematics with the other sciences.X