COURSE UNIT TITLE

: STATISTICAL RESEARCH METHODOLOGY I

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
STA 5059 STATISTICAL RESEARCH METHODOLOGY I 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

Offered to

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

Course Objective

Understand basic probability distributions and data management, data exploration, and descriptive and inferential statistics. Apply and comment to Statistical analysis.

Learning Outcomes of the Course Unit

1   Data Definition and Managing Data
2   Calculating Descriptive Statistics
3   Making Tables and Graphics
4   Write a macro
5   Make statistical inferences

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Statistics, Data and Statistical Thinking
2 Fundamental Elements of Statistics
3 Graphical Methods Methods and Numerical Measures for Describing Sets of Data
4 Constructing Frequency Distributions, Graphs for Qualitative and Quantitative Data
5 Measures of Central Tendency and Measures of Variability
6 Introduction to Macros
7 Macros for Measures of Central Tendency and Measures of Variability
8 Midterm exam
9 Discrete Random Variables and Discrete Probability Distributions
10 Continuous Random Variables and Continuous Probability Distributions
11 Macros for Probability Distributions,homework
12 Statistical Inference and Sampling
13 Sampling Distributions (Z, Chi-square, t, F), Central Limit theorem
14 Hypothesis tests, Power, Type I and Type II Errors

Recomended or Required Reading

Textbook(s):
1. McClave J.T., Sincich T., Statistics, 11th edition, Prentice Hall,USA, 2008
2. Ryan,B., Joiner, B.L. & Cryer, J.D., MINITAB Handbook, 5th edition, Brooks/Cole - Thomson Learning Inc, Duxbury, Canada, 2005

Planned Learning Activities and Teaching Methods

Lecture, homework 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 * 0.40 +ASG * 0.10 +FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 +ASG * 0.10 +RST * 0.50


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

Further Notes About Assessment Methods

If the instructor needs to add some explanation or further note, this column can be selected from the DEBIS menu.

Assessment Criteria

Evaluation of homework and exams

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. You can find the undergraduate policy at http://www.fbe.deu.edu.tr.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 1 14
Preparation for midterm exam 1 40 40
Preparation for final exam 1 45 45
Preparing assignments 1 25 25
Midterm 1 2 2
Final 1 2 2
TOTAL WORKLOAD (hours) 170

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.15555555555
LO.25555555555
LO.35555555555
LO.45555555555
LO.55555555555

CONTACT INFORMATION
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Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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