COURSE UNIT TITLE

: DATA ANALYSIS AND STATISTICAL INFERENCE

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
EES 5049 DATA ANALYSIS AND STATISTICAL INFERENCE ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR DOĞAN YAŞAR

Offered to

ENVIRONMENTAL EARTH SCIENCES
ENVIRONMENTAL EARTH SCIENCES-NON THESIS

Course Objective

Several problems encountered in various branches of engineering relate to natural
processes which are governed by the laws of chance and which, therefore, are subject to
uncertainty. Such problems can only be studied by the use of probability theory and
mathematical statistics to take into account the uncertainty so that reliable and
economic solutions can be achieved. Probability theory and mathematical statistics
comprise the analysis of data observed on the uncertain processes, where the objective
is the extraction of information from data by statistical inference. This course is
intended to introduce the basic and essential concepts in data analysis, to present the
techniques used and to discuss the application of these techniques to natural processes
on various examples.

Learning Outcomes of the Course Unit

1   understand the techniques used and discuss the application of these techniques to
2   introduce the basic and essential concepts in data analysis

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to Statistical and Probability Methods
2 Characteristics of Random Processes
3 Random Variables and Their Distributions
4 Basic Concepts of Probability Theory
5 Methods of Parameter Estimation
6 Frequency Analysis
7 Probability Distributions
8 Probability Distributions and Tests of Goodness of Fit
9 I. MIDTERM EXAM
10 Sampling Theory and Decision Making (Hypothesis Testing)
11 Correlation and Regression Analyses
12 Correlation and Regression Analyses
13 II. MIDTERM EXAM
14 Presentation of Assignments and Evaluation

Recomended or Required Reading

Walpole, R.E. & Myers, R.H. (1990): Probability and Statistics for Engineers and
Scientists (4th ed.). MacMillan Publishing Company, New York, 765 s.

Planned Learning Activities and Teaching Methods

Homeworks and presentations

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 FIN FINAL EXAM
3 FCG FINAL COURSE GRADE MTE * 0.50 + FIN * 0.50
4 RST RESIT
5 FCGR FINAL COURSE GRADE MTE * 0.50 + RST * 0.50


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

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

To be announced.

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 5 70
Preparation for midterm exam 2 10 20
Preparation for final exam 1 20 20
Preparing assignments 1 20 20
Preparing presentations 1 10 10
Midterm 2 2 4
Final 1 2 2
TOTAL WORKLOAD (hours) 188

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12
LO.1121212211343
LO.2121212112333

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

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