COURSE UNIT TITLE

: STATISTICS II

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
END 2404 STATISTICS II COMPULSORY 3 0 0 5

Offered By

Industrial Engineering

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSISTANT PROFESSOR ŞEBNEM DEMIRKOL AKYOL

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 concepts of inferential statistics such as parameter estimation, hypothesis testing, one and two factor experiments, simple linear regression and correlation, multiple linear regression and nonparametric statistical analysis.

Learning Outcomes of the Course Unit

1   State, explain and interpret relevant inferential statistics for various data sets
2   Explain parameter estimation for point and confidence intervals
3   State and explain statistical hypothesis tests
4   State and explain variance analysis
5   State and explain regression analysis
6   Explain the usage of Minitab software for inferential statistical analysis

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

END 2303 - STATISTICS I

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to Statistics II
2 Parameter estimation I; point estimation
3 Parameter estimation II; confidence interval estimation-Mean and difference of means
4 Parameter estimation III; confidence interval estimation-Variance, variance ratios, ratio and difference of ratios, statistical calculations with Minitab software
5 Hypothesis testing I: Mean and difference of means
6 Hypothesis testing II: Variance, ratio and difference of ratios, statistical calculations with Minitab software
7 One Factor experimental design and analysis I
8 One Factor experimental design and analysis II, statistical calculations with Minitab software
9 Mid-Term Exam
10 Two Factor experimental design and analysis I
11 Two Factor experimental design and analysis II
12 Simple linear regression and correlation
13 Multiple linear regression and polynomial regression, statistical calculations
14 Project presentations

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 futher supported by computer lab work.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 PRJ PROJECT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + PRJ * 0.20 + FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + PRJ * 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

To be announced.

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
Preparation for midterm exam 1 15 15
Preparation for final exam 1 15 15
Preparing assignments 1 4 4
Preparations before/after weekly lectures 13 3 39
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.11
LO.14
LO.24
LO.355
LO.4545
LO.554
LO.645