COURSE UNIT TITLE

: POWER ANALYSIS OF STATISTICAL METHODS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
STA 5025 POWER ANALYSIS OF STATISTICAL METHODS ELECTIVE 3 0 0 7

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR ABDULLAH FIRAT ÖZDEMIR

Offered to

Statistics (English)
STATISTICS (ENGLISH)
Statistics (English)

Course Objective

The objective of this course is to cover an intermediate level of Statistical Design of Experiments

Learning Outcomes of the Course Unit

1   The Power of Statistical Tests
2   The Mechanics of Power Analysis
3   Hypothesis Tests versus Confidence Intervals
4   A Simple and General Model for Power Analysis
5   Alternatives to the Traditional Null Hypothesis
6   Analytic and Tabular Methods of Power Analysis
7   Using Power Analysis
8   Multifactor ANOVA and Repeated Measures Studies

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 1-)The Structure of Statistical Tests
2 2-)The Mechanics of Power Analysis, Preparing Individual Assignments
3 3-)A Simple and General Model for Power Analysis
4 4-)The F Distribution and Power, Preparing Individual Assignments
5 5-)Translating Common Statistics and Effect Size Measures Into F
6 6-)Alternatives to the Traditional Null Hypothesis
7 7-)Minimum Effect Tests As Alternatives to Traditional
8 8-)Analitic and Tabular Methods of Power Analysis
9 9-)Effect Size Conventions for Defining Minimum Effect Hypothesis, Preparing Individual Assignments
10 10-)Estimating the Effect Size
11 11-)Four Applications of Statistical Power Analysis, Preparing Individual Assignments
12 12-)Multifactor ANOVA and Repeated Measures Studies
13 13-)The Multivariate Analysis of Variance
14 14-)A general review

Recomended or Required Reading

Textbook(s): Kevin R. Murphy and Brett Myors, Statistical Power Analysis by, Lawrence Erlbaum, 2004

Planned Learning Activities and Teaching Methods

Lecture format, built around the textbook readings and computer applications with numerous examples chosen to illustrate theoretical concepts. Lots of drill with emphasis on practice. Questions are encouraged and discussion of material stressed.Lecture and problem solving.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + ASG * 0.40 + FIN * 0.30
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + MAKRASG * 0.40 + MAKRRST * 0.30


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

Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of homework assignments 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)

DEU Fen Fakültesi Istatistik Bölümü
e-mail: firat.ozdemir@deu.edu.tr
Tel: 0232 301 85 52

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparation for midterm exam 1 12 12
Preparation for final exam 1 36 36
Preparations before/after weekly lectures 14 2 28
Preparing assignments 4 14 56
Midterm 1 2 2
Final 1 2 2
Quiz etc. 1 2 2
TOTAL WORKLOAD (hours) 180

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.1555
LO.2555
LO.3555
LO.4555
LO.5555
LO.6555
LO.7555
LO.8555