COURSE UNIT TITLE

: ENGINEERING STATISTICS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
END 2414 ENGINEERING STATISTICS COMPULSORY 3 1 0 5

Offered By

Industrial Engineering

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR GONCA TUNÇEL MEMIŞ

Offered to

Industrial Engineering

Course Objective

The main purpose of this course is to introduce students to inferential statistics concepts such as parameter estimation, hypothesis testing, single and two-factor experiments, simple linear regression and correlation, and multiple linear regression to use in various professional problems they will encounter.

Learning Outcomes of the Course Unit

1   To calculate and interpret sample and population statistics by performing inferential statistical analysis on various data.
2   To calculate and interpret parameter estimates for points and confidence intervals
3   To create hypotheses and interpret hypothesis test results
4   To apply single-factor and double-factor analysis of variance
5   To apply regression analysis
6   To use software for inferential statistical analysis

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

END 2313 - INTRODUCTION TO PROBABILITY AND STATISTICS

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to engineering statistics
2 Parameter estimation I; Point Estimation
3 Parameter estimation II; Confidence interval estimate - Mean and difference between two means
4 Parameter estimation III; Confidence interval estimation-Variance, variance ratios, ratio and difference between two ratios, Software application
5 Hypothesis tests I: Mean and difference between two means
6 Hypothesis tests II: Variance, ratio and difference between two ratios
7 Software application
8 Design and analysis of single-factor experiments I
9 Design and analysis of single-factor experiments II
10 Design and analysis of two-factor experiments I
11 Design and analysis of two-factor experiments II
12 Software application
13 Simple linear regression and correlation
14 Multiple linear regression and polynomial regression

Recomended or Required Reading

1. D. C. Montgomery and G.C. Runger, (1999). Applied Statistics and Probability for Engineers, 2nd Edition. John Wiley and Sons, USA.
2. R. E. Walpole, R. H. Myers, S. L. Myers, (1998). Probability and Statistics for Engineers and Scientists, 6th Edition. Prentice Hall, USA.
3. F. Akdeniz. (2010). Olasılık ve Istatistik, 15.Baskı. Nobel Yayın Dağıtım, Adana.

Planned Learning Activities and Teaching Methods

Presentations, homeworks, software applications

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 * 0.20 + FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + ASG * 0.20 + RST * 0.50


Further Notes About Assessment Methods

None

Assessment Criteria

Mid-term (30%)+Homework (20%)+Final Exam (50%)

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

gonca.tuncel@deu.edu.tr
0232 301 46 17

Office Hours

Tuesday-Thursday 13:30-16:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 11 4 44
Labratory 3 4 12
Group homework preperation 5 15 75
Midterm 1 2 2
Final 1 2 2
TOTAL WORKLOAD (hours) 135

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.11
LO.2132
LO.3132
LO.41325
LO.51
LO.63

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

Copyright 2015 DEÜ. BİD

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