Course Information


Course Information
Course Title Code Semester L+U Hour Credits ECTS
STATISTICAL INFERENCE IN ACTUARIES UAKT202 4. Semester 2 + 2 3.0 6.0

Prerequisites None

Language of Instruction Turkish
Course Level Bachelor's Degree
Course Type Compulsory
Mode of delivery Computer aided oral presentation
Course Coordinator
Instructors
Assistants
Goals To teach how to estimate and test the unknown population parameters from sample. For this purpose, to give detailed information about interval estimation and hypothesis tests. Besides, to describe methods of analysis of variance, regression and correlation in quantitative data sets. Finally, to give information about non parametric statistical methods.
Course Content Investigating the properties of the estimators based on the sample. Statistical inference for population parameters.
Learning Outcomes 1) Learns some important issues such as statistical estimation, point estimation and interval estimation
2) Knows the important features of a good estimators
3) Learns some special methods used to obtain the best estimator
4) Learns the calculation of confidence intervals for mean, ratio and variance
5) Learns the construction and testing hypotheses related to mean, ratio and variance
6) Acquires summary information about non-parametric statistical methods

Weekly Topics (Content)
Week Topics Teaching and Learning Methods and Techniques Study Materials
1. Week Order Statistics Lecture; Question Answer; Problem Solving

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
2. Week Point Estimation Lecture; Question Answer; Problem Solving

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
3. Week Mean Square Error Lecture; Question Answer; Problem Solving

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
4. Week Minimum Variance Unbiased Estimates – Rao-Cramer Inequality Lecture; Question Answer; Problem Solving

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
5. Week Sufficient Statistics Lecture; Question Answer; Problem Solving

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
6. Week Maximum Likelihood Estimator Lecture; Question Answer; Problem Solving

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
7. Week Maximum Likelihood Estimator Lecture; Question Answer; Problem Solving

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
8. Week Midterm exam

9. Week Interval Estimation Lecture; Question Answer; Problem Solving

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
10. Week Theoretical Hypothesis Testing Lecture; Question Answer; Problem Solving

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
11. Week Ciritical Region – Neyman-Pearson Theorem Lecture; Question Answer; Problem Solving

 Homework
12. Week Hypothesis Tests for the Mean Of Normal Distribution Lecture; Question Answer; Problem Solving

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
13. Week Hypothesis Tests for Variance Lecture; Question Answer; Problem Solving

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
14. Week Comparison of k Binomial Distribution Lecture; Question Answer; Problem Solving

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
15. Week Goodness of Fit Tests Lecture; Question Answer; Problem Solving

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
16. Week Fina exam


Sources Used in This Course
Recommended Sources
Dennis,D., Wackerly and William Mendenhall,R.L., 1996, Mathematical Statistics with Applications, Duxbury Press, USA.
Hogg, R.V., Craig, A.T., 1995, Introduction to Mathematical Statistics, Collier MacMillan.
İnal, C., Günay, S., 2010, Olasılık ve Matematiksel İstatistik, Hacettepe Yayınları, Ankara
Nguyen, H.T., Regers, G. S., Fundamentals of Mathematical Statistics, Springer – Verlag, 1989.
Ross,S., 1998, A First Course in Probability, Prentice Hall, New Jersey.

Relations with Education Attainment Program Course Competencies
Program RequirementsContribution LevelDK1DK2DK3DK4DK5DK6
PY15000000
PY25000000
PY35000000
PY45000000
PY55000000

*DK = Course's Contrubution.
0 1 2 3 4 5
Level of contribution None Very Low Low Fair High Very High
.

ECTS credits and course workload
Event Quantity Duration (Hour) Total Workload (Hour)
Course Duration (Total weeks*Hours per week) 14 4
Work Hour outside Classroom (Preparation, strengthening) 14 4
Homework 5 3
Midterm Exam 1 2
Time to prepare for Midterm Exam 1 24
Final Exam 1 2
Time to prepare for Final Exam 1 24
Total Workload
Total Workload / 30 (s)
ECTS Credit of the Course
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Course Information
  • Course Information
  • Weekly Topics (Content)
  • Sources Used in This Course
  • Relations with Education Attainment Program Course Competencies
  • ECTS credits and course workload