COURSE UNIT TITLE

: STATISTICS I

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
END 2303 STATISTICS I COMPULSORY 3 0 0 5

Offered By

Industrial Engineering

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASISTANT PROFESSOR SEREN ÖZMEHMET TAŞAN

Offered to

Industrial Engineering Scientific Preparatory (Msc)
Industrial Engineering Scientific Preparatory (Msc Without Thesis)
Industrial Engineering Scientific Preparatory (Phd)
Industrial Engineering

Course Objective

To obtain an understanding and ability to use basic statistics, random variables and descriptive statistics.

Learning Outcomes of the Course Unit

1   Explain the basic elements, principles and techniques of statistics with terminology.
2   Explain elements of probability concept and probability distributions
3   State and explain statistics related to random variables
4   State and explain relevant figures and graphs for various data sets
5   Analyze and interpret data sets with descriptive statistics
6   Explain the usage of Minitab software for descriptive 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 to Statistics I and Ethics
2 Probability Rules and Random Variables
3 Discrete Random Variables: Probability Density Function, Expected Value and Variance
4 Continuous Random Variables: Probability Density Function, Expected Value and Variance
5 Bivariate Random Variables I: Probability Density Function, Marginal Functions, Expected Value and Variance
6 Bivariate Random Variables II: Independence, Conditional Density, Covariance and Correlation
7 Special Discrete Random Variables I: Discrete Uniform Dist., Bernoulli Dist., Binomial Dist., Negative Binomial Dist.
8 Special Discrete Random Variables II: Hypergeometric Dist., Poisson Dist.
9 Mid-Term Exam
10 Special Continuous Random Variables I: Continuous Uniform Dist., Gamma Dist., Exponential Dist.
11 Special Continuous Random Variables II: Normal Dist., Chi-square Dist., t Dist., F Dist.
12 Relationship between Population and Sampling
13 Random Sampling, Histograms, Sample Statistics
14 Statistical calculations with Minitab software

Recomended or Required Reading

Textbooks:
1. D. C. Montgomery and G.C. Runger, (1999). Applied Statistics and Probability for Engineers, 2nd Edition. John Wiley and Sons, USA.

Reference books:
1. R. E. Walpole, R. H. Myers, S. L. Myers, (1998). Probability and Statistics for Engineers and Scientists, 6th Edition. Prentice Hall, USA.
2. Fikri Akdeniz. (2010). Olasılık ve Istatistik, 15.Baskı. Nobel Yayın Dağıtım, Adana.

Planned Learning Activities and Teaching Methods

Instructor notes will be given using blackboard and visual presentations. Additionally, it will be further supported by computer lab work.

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 (RESIT) MTE * 0.50 + RST * 0.50


Further Notes About Assessment Methods

None

Assessment Criteria

Midterm exam (50%)+Final exam (50%)

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Tel: 301 76 22
e-mail: seren.ozmehmet@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Tutorials 1 3 3
Preparations before/after weekly lectures 13 3 39
Preparation for midterm exam 1 15 15
Preparation for final exam 1 15 15
Preparing assignments 1 4 4
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 119

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12
LO.153
LO.24
LO.34
LO.4554
LO.555543
LO.65