Dokuz Eylül University Information Package / Courses Catalog

Description of Individual Course Units

Course Unit Code	Course Unit Title	Type Of Course	D	U	L	ECTS
FPE 0056	ESTIMATION AND HYPOTHESIS TESTING	ELECTIVE	4	0	0	6

Offered By

Faculty Of Science

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR BURCU HÜDAVERDI

Offered to

Biology
Chemistry
Computer Science
Statistics
Mathematics
Physics
Faculty Of Science

Course Objective

The main goal is that students learn the basic concepts and methods of parametric statistical inference, emphasizing the importance of the normal distribution when obtaining estimators and testing hypothesis about population parameters. The students should be able to apply these procedures to solve practical problems.

Learning Outcomes of the Course Unit

1	Explain the concepts of random sample and statistics
2	Define the fundamental sampling distributions and its properties
3	Understand how to derive point estimators and their properties
4	Understand the theory behind confidence intervals
5	Understand the theory behind hypothesis testing and basic concepts of it (simple and composite hypotheses, rejection region, Type I and Type II error, power function, etc.)
6	Use the theory behind normal-based inference procedures for the one and two-sample problems
7	Obtain the most powerful critical region and most powerful test for simple hypothesis

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week	Subject	Description
1	Concepts of random and statistical sample.
2	Convergence concepts (Central limit theorem, Law of Large Numbers)
3	Sampling Distributions(Z, ki-kare, t, F)
4	Point Estimation, Point Estimation Methods (Method of Moments, Maximum Likelihood Method)
5	Properties of estimator (Bias and Variance; Mean-squared error)
6	Properties of estimator (Cramer-Rao inequality, efficiency, consistency and other asymptotic properties)
7	Sufficient Statistics
8	Midterm exam
9	Interval Estimation and Pivotal Quantity
10	Confidence Interval Based on One-Sample
11	Confidence Interval Based on Two-Sample
12	Basic concepts of hypothesis testing (simple and composite hypotheses, rejection region, Type I and Type II error) / Power function and power of the test
13	The theory behind normal-based inference procedures for one/two sample problems
14	Most Powerful Test / Most powerful critical region for simple hypothesis

Recomended or Required Reading

Main textbook:
L. J. Bain and M. Engelhardt, Introduction to Probability and Mathematical Statistics, 2nd Edition, Duxbury, 1992.

Supplementary Book(s):
R. J. Larsen and M. L. Marx, An Introduction to Mathematical Statistics and Its Applications, 4th Edition, Prentice Hall.
I. Miller and M. Miller, John E. Freund's Mathematical Statistics with Applications, 7 edition Prentice Hall, 2003.

Planned Learning Activities and Teaching Methods

Lecture format, built around the textbook readings, applications and examples. Questions and discussion are encouraged. Lecture, homeworks and exams.

Assessment Methods

SORTING NUMBER	SHORT CODE	LONG CODE	FORMULA
1	MTE	MIDTERM EXAM
2	QUZ	QUIZ
3	FIN	FINAL EXAM
4	FCG	FINAL COURSE GRADE	MTE * 0.30 + QUZ * 0.20 + FIN * 0.50
5	RST	RESIT
6	FCGR	FINAL COURSE GRADE (RESIT)	MTE * 0.30 + QUZ * 0.20 + RST * 0.50

*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Midterm exam, quiz, homework and final exam.

Language of Instruction

English

Course Policies and Rules

Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture and homework delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy.

Contact Details for the Lecturer(s)

Prof. Dr. Burcu Hüdaverdi
e-mail: burcu.hudaverdi@deu.edu.tr
tel: +90-232-3018597

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities	Number	Time (hours)	Total Work Load (hours)
Lectures	11	2	22
Tutorials	2	2	4
Preparations before/after weekly lectures	13	2	26
Preparation for midterm exam	1	15	15
Preparation for final exam	1	30	30
Preparation for quiz etc.	2	15	30
Preparing assignments	2	12	24
Midterm	1	2	2
Final	1	2	2
Quiz etc.	2	1	2
TOTAL WORKLOAD (hours)			157

Contribution of Learning Outcomes to Programme Outcomes

PO/LO	PO.1	PO.2	PO.3	PO.4	PO.7	PO.12	PO.13
LO.1	2	1	2	2	2	2	3
LO.2	2	1	2	2	2	2	3
LO.3	2	1	2	2	2	2	3
LO.4	2	1	2	2	2	2	3
LO.5	2	1	2	2	2	2	3
LO.6	2	1	2	2	2	2	3
LO.7	2	1	2	2	2	2	3

COURSE UNIT TITLE

DEGREE PROGRAMMES

Description of Individual Course Units

Offered By

Level of Course Unit

Course Coordinator

Offered to

Course Objective

Learning Outcomes of the Course Unit

Mode of Delivery

Prerequisites and Co-requisites

Recomended Optional Programme Components

Course Contents

Recomended or Required Reading

Planned Learning Activities and Teaching Methods

Assessment Methods

Further Notes About Assessment Methods

Assessment Criteria

Language of Instruction

Course Policies and Rules

Contact Details for the Lecturer(s)

Office Hours

Work Placement(s)

Workload Calculation

Contribution of Learning Outcomes to Programme Outcomes

CONTACT INFORMATION