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GRADUATE INSTITUTE of SOCIAL SCIENCES / DEPARTMENT of ECONOMETRICS
Masters With Thesis
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SBE
GRADUATE INSTITUTE of SOCIAL SCIENCES / DEPARTMENT of ECONOMETRICS / Masters With Thesis
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EKOZ5520Statistical Methods3+0+0ECTS:7.5
Year / SemesterSpring Semester
Level of CourseSecond Cycle
Status Compulsory
DepartmentDEPARTMENT of ECONOMETRICS
Prerequisites and co-requisitesNone
Mode of Delivery
Contact Hours14 weeks - 3 hours of lectures per week
LecturerProf. Dr. Tuba YAKICI AYAN
Co-LecturerProf. Dr. Mustafa KÖSEOĞLU
Language of instructionTurkish
Professional practise ( internship ) None
 
The aim of the course:
The aim of the course is to present statistical inference methods practically.
 
Programme OutcomesCTPOTOA
Upon successful completion of the course, the students will be able to :
PO - 1 : understand some estimation and hypothesis test methods101,
PO - 2 : explain some estimation and hypothesis test methods101,
PO - 3 : apply some estimation and hypothesis test methods101,
PO - 4 : determine the appropriate estimation and hypothesis test methods101,
PO - 5 : infer about the population.101,
CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), PO : Learning Outcome

 
Contents of the Course
Sampling Theory, Estimation Theory , Testing Hypotheses, The Chi-Square Tests, Analysis of Variance, Regression and Correlation, Some Nonparametric Tests
 
Course Syllabus
 WeekSubjectRelated Notes / Files
 Week 1Sampling Theory: Population and parametesr, random sample and sample statistics, sampling distributions, central limit theorem, statistical inference
 Week 2Estimation Theory: Point estimate and interval estimate, precision, reliability, confidence interval for the mean, determining the required sample size for estimating the mean, confidence interval for the difference between two means
 Week 3Estimation Theory: Confidence interval for the population proportion, determining required sample size for estimating the proportion, confidence interval for the variance
 Week 4Hypothesis Testing: Basic steps in hypothesis testing, type I and typ II errors, hypothesis testing concerning the mean
 Week 5Hypothesis testing: Hypothesis testing difference between two means based on paired observations, hypothesis testing concerning the proportion and the variance
 Week 6Hypothesis Testing: Goodness of fit tests, chi-square test for independence and homogenity
 Week 7Analysis of Variance: One-way analysis of variance, two-way analysis of variance (one observation per cell)
 Week 8 Analysis of Variance: Two way analysis of variance (n observations per cell), analysis of variance for three factors
 Week 9Mid-term exam
 Week 10Regression and Correlation Analysis: The simple linear regression analysis
 Week 11The matrix approach to simple linear regression analysis
 Week 12Quiz
 Week 13 The matrix approach to multiple regression analysis
 Week 14Multicollinearity, heterocedasticity, autocorrelation
 Week 15Some Nonparametric Tests: The runs test of randomness, sign test (one sample and paired obsevations), the wilcoxon test (one sample and paired obsevations), the mann-whitney test
 Week 16End-of-term exam
 
Textbook / Material
1Newbold, P. (çev. Şenesen, Ü.) 2000; İşletme ve İktisat için İstatistik, Literatür Yayıncılık, İstanbul
2Türedi, N. 2004; Uygulamalı İstatistik Yöntemler, Celepler Matbaacılık, Trabzon
 
Recommended Reading
 
Method of Assessment
Type of assessmentWeek NoDate

Duration (hours)Weight (%)
Mid-term exam 9 04/2024 1,15 30
Presentation 12 05/2024 20
End-of-term exam 16 06/2024 1,15 50
 
Student Work Load and its Distribution
Type of workDuration (hours pw)

No of weeks / Number of activity

Hours in total per term
Yüz yüze eğitim 3 14 42
Sınıf dışı çalışma 8 14 112
Arasınav için hazırlık 15 2 30
Arasınav 2 1 2
Dönem sonu sınavı için hazırlık 19 2 38
Dönem sonu sınavı 1 1 1
Total work load225