# COURSE UNIT TITLE

: STATISTICAL TECHNIQUES FOR ENGINEERING MANAGEMENT

#### 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)

#### Offered to

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

#### 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

Face -to- Face

None

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#### 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

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

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#### Assessment Criteria

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

English

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

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