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COURSE UNIT TITLECOURSE UNIT CODESEMESTERTHEORY + PRACTICE (Hour)ECTS
INSURANCE STATISTICS SRU502 Second Term (Spring) 3 + 0 10

TYPE OF COURSE UNITCompulsory Course
LEVEL OF COURSE UNITMaster's Degree Without Thesis
YEAR OF STUDY1
SEMESTERSecond Term (Spring)
NUMBER OF ECTS CREDITS ALLOCATED10
NAME OF LECTURER(S)Professor Serpil Cula
LEARNING OUTCOMES OF THE COURSE UNIT At the end of this course, the students;
1) Compare different data groups
2) Think analytically, make synthesis and associate
3) Make future projections and make inferences by analyzing data
4) Construct cause effect realtionship between variables, make inference and decide
5) Examine the relationships between insurance and actuary variables
MODE OF DELIVERYE-Learning
PRE-REQUISITES OF THE COURSENo
RECOMMENDED OPTIONAL PROGRAMME COMPONENTNone
COURSE DEFINITIONMain objective of the course, is to gain ability of establish linear or nonlinear regression model on any finance subject and also to evaluate the figures of anova analysis. Students will gain the ability of using statistical techniques to establish their research questions, pose relevant hypotheses, and make use of the most appropriate tests to carry out a scientific study by applictions on eviews ."
COURSE CONTENTS
WEEKTOPICS
1st Week Introduction, probabilistic and statistical basic concepts
2nd Week Discrete random variables and distributions
3rd Week Continuous random variables and distributions
4th Week Basic satistical measures
5th Week Statistical distributions using in insurance
6th Week Insurance data analysis
7th Week Risk premium
8th Week Midterm
9th Week Pricing in insurance
10th Week Credibility theory
11th Week Baye's theorem
12th Week Simulation
13th Week Loss reserve estimatio in insurance
14th Week Porfolio analysis in elementary risk analysis
RECOMENDED OR REQUIRED READINGI.B. Hossack, J.H. Pollard, B. Zenwirth, Introductory Statistics with Applications in General Insurance.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODSLecture,Discussion,Questions/Answers,Problem Solving,Project
ASSESSMENT METHODS AND CRITERIA
 QuantityPercentage(%)
Assignment120
Total(%)20
Contribution of In-term Studies to Overall Grade(%)20
Contribution of Final Examination to Overall Grade(%)80
Total(%)100
ECTS WORKLOAD
Activities Number Hours Workload
Midterm exam
Preparation for Quiz
Individual or group work1412168
Preparation for Final exam16565
Course hours14342
Preparation for Midterm exam
Laboratory (including preparation)
Final exam122
Homework13030
Total Workload307
Total Workload / 3010,23
ECTS Credits of the Course10
LANGUAGE OF INSTRUCTIONTurkish
WORK PLACEMENT(S)No
  

KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)
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K5  X     X   X   X
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K9    X      
K10    X