COURSE UNIT TITLE

: INTRODUCTION TO STATISTICS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
TEX 2009 INTRODUCTION TO STATISTICS COMPULSORY 2 0 0 3

Offered By

Textile Engineering

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR MUSA KILIÇ

Offered to

Textile Engineering

Course Objective

1 Teaching of basic statistical knowledge
2 Teaching of data collection, data summarization and data presentation techniques
3 Information about some specific probability distributions and their properties
4 Information about statistical inference and decision-making processes
5 Information about the relationships between the variables

Learning Outcomes of the Course Unit

1   To be able to define the basic concepts related to statistics
2   Summarizing and presenting the data obtained as a result of experiments and observations
3   Ability to calculate descriptive statistics for a data set
4   To be able to interpret and compare by using statistical results.
5   To be able to define and predict relationships between variables.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Basic Concepts: Explanation of the concepts such as statistics, variable, variation, population, observation, data, sample.
2 Summarizing and Presentation of Data: Creating a frequency table, graphical summarization and presentation of data
3 Descriptive Sample Statistics: Measures of central tendency (mean, mode, median etc.) and measures of variation (variance, standard deviation, coefficient of variation, etc.). Coding data for statistical calculations (additive, multiplicative and combined coding)
4 Theory Probability: Repeatable event, sample space, relative frequency, explanation of probability concepts.
5 Random Variables: Classification of random variables and the concept of expected value
6 Probability Distributions for Discrete Variables: Binomial tests and Binomial distribution.
7 Probability Distributions for Discrete Variables: Poisson Distribution
8 1st Midterm Exam
9 Probability Distributions for Continuous Variables: Normal distribution and its properties
10 Statistical Inference: Point and interval estimation for population mean (confidence intervals)
11 Test of Hypothesis: Establishing and testing a hypothesis. Comparison of the population mean with a fixed value (Large and small sample tests)
12 Test of Hypothesis: Comparison of two population means (Large and small sample tests) Variance Analysis Concept
13 2nd Midterm Exam
14 Relationships Between Variables: Regression and Correlation

Recomended or Required Reading

1. Istatistiğe Giriş, 7. Baskı, Fikret Ikiz, Halis Püskülcü, Şaban Eren, Barış Yayınları - Fakülteler Kitabevi, 2006.
2. Introductory Statistics, Third Edition, Sheldon M. Ross, Academic Press, ISBN: 9780123743886, 2010.
3. Applying Regression & Correlation, J. Miles, M. Shevlin, Sage Publications Ltd.,0-7619-6229-8, 2004.
4. Introduction to Engineering Statistics and Six Sigma, Theodore T. Allen, Springer, 1-85233-955-1, Germany, 2006.

Planned Learning Activities and Teaching Methods

Presentation

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 * 0.25 + ASG * 0.25 + FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.25 + ASG * 0.25 + RST * 0.50


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

Further Notes About Assessment Methods

To be successful from midterm exam, assignment and final exam.

Assessment Criteria

To continue the courses within the framework of the regulation, to be successful in the midterm and final exams.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Assoc. Prof. Dr. Musa KILIC

Dokuz Eylül University
Faculty of Engineering
Department of Texile Engineering
Tınaztepe Campus
35397 Buca - IZMIR

Tel : 0232 301 77 14
E-Mail : musa.kilic@deu.edu.tr
Web : people.deu.edu.tr/musa.kilic

Office Hours

According to the curriculum, it will be announced to students during the semester.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 2 24
Preparations before/after weekly lectures 12 1 12
Preparation for midterm exam 1 8 8
Preparation for final exam 1 10 10
Preparing assignments 1 8 8
Midterm 1 2 2
Final 1 2 2
Project Assignment 1 2 2
TOTAL WORKLOAD (hours) 68

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.133
LO.245444
LO.335454
LO.455544
LO.545455