COURSE UNIT TITLE

: STATISTICAL TECHNIQUES FOR ENGINEERING MANAGEMENT

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
ENM 5038 STATISTICAL TECHNIQUES FOR ENGINEERING MANAGEMENT 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 ADIL BAYKASOĞLU

Offered to

M.Sc. Metallurgical and Material Engineering
Metallurgical and Material Engineering
ENGINEERING MANAGEMENT- NON THESIS (EVENING PROGRAM)
Metallurgical and Material Engineering

Course Objective

The goal of this course is to introduce students the basis of descriptive statistics, elementary probability theory (random variables, discrete and continuous probability models), statistical inference (point estimation, interval estimation, and tests of hypotheese), and other statistical methods (linear regression and correlation, ANOVA and so on). After completing this course, students will be able to determine which statistic and /or method is appropriate for a given situation and to make statistical inferences about a population by using the sample from that population.

Learning Outcomes of the Course Unit

1   To comprehend the properties of probability
2   To learn how to analyze statistical data properly.
3   To understand the implications of study design on the type of statistical inference
4   To identify a statistical technique appropriate to address a given research question
5   To apply the appropriate statistic and/or method to real world business problems
6   To communicate clearly and correctly the results of the statistical analysis

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction: Basic probability concepts, definitions of probability
2 Data Collection for Statistical Analysis, and Presenting Data in Tables and Charts (Frequency Distribution Tables and Graphs), Measures of central tendency and variability
3 Random variable. Discrete random variable and its features. Continuous random variable and its features.
4 Discrete theoretical distributions: Uniform distribution, Bernoulli distribution, Binomial distribution, Hypergeometric distribution, Poisson distribution
5 Continuous theoretical distributions: The Normal Distribution and Sampling Distributions
6 Confidence Interval Estimation
7 Fundamentals of Hypothesis Testing: One-Sample Tests
8 Two-Sample Tests with Numerical Data
9 Mid-Term Exam
10 Regression (Simple linear regression, estimation of regression parameters, Coefficient of determination, correlation coefficient)
11 Multiple Regression Models
12 Analysis of variance
13 Statistical Applications in Quality and Productivity Management
14 Decision Making

Recomended or Required Reading

Statistics for Managers (1999); David M. Levine, Mark L. Berenson, and David Stephan. Prentice Hall, USA.

Statistics for Business and Economics (2001); James T. McClave, P. George Benson, and Terry Sincich. Prentice Hall, USA.

A First Course In Business Statistics (2001); James T. McClave, P. George Benson, and Terry Sincich. Prentice Hall, USA.

Planned Learning Activities and Teaching Methods

Lectures, problem classes, worksheets, course notes, textbooks, web support, and laboratory work.

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


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

Further Notes About Assessment Methods

None

Assessment Criteria

Mid term exam (% 35) + Research/term project (%15) + Final exam (%50)

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

E-mail: gonca.tuncel@deu.edu.tr

Telf: 0232 301 76 17

Office Hours

Tuesday-Thursday, 13:00-17:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparation before/after weekly lectures 13 6 78
Preparation for Mid-term Exam 1 12 12
Preparation for Final Exam 1 15 15
Preparing Presentations 1 10 10
Preparing Individual Assignments 5 7 35
Final exam 1 2 2
Mid-term 1 2 2
TOTAL WORKLOAD (hours) 193

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.14554324
LO.2
LO.35455335
LO.4
LO.544443
LO.632253

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

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