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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS UKY 8035 PROBABILITY AND STATISTICS ELECTIVE 3 0 0 6

Offered By

Quality Management Non-thesis (Distance Learning)

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR GÜLÜZAR KURT GÜMÜŞ

Offered to

Quality Management Non-thesis (Distance Learning)

Course Objective

Objectives of this course are: 1. to learn the critical effects of variability within business processes. 2. to learn how to collect and organize the process data. 3. to study distributions of data. 4. to learn special distributions for statistical analyses. 5. to learn hypothesis test approaches for desicion making.

Learning Outcomes of the Course Unit

1   knows variabilty concept and effect of this on processes. 2   knows statistical concepts such as population, parameter and sample. 3   knows how to collect, summerize and present the process data. 4   knows random variable concept and how to study the distribution of random variable. 5   knows estimation concept and how to construct and interprete confidence intervals. 6   knows how to construct and execute hypothesis tests for desicion making.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Variation concept and quality 2 Basic concepts (population, parameter, sample etc.) 3 summarizing and presenting data 4 measures of location 5 measures of dispersion and skewness 6 basic probability 7 modelling process variability and random variables. 8 discrete and continuous random variables 9 special probability distributions - Binomial, Poisson 10 special probability distributions - Uniform, exponential, normal 11 estimators and confidence intervals 12 estimators and confidence intervals 13 hypothesis tests 14 hypothesis tests

Recomended or Required Reading

Işletme ve iktisat için istatistik Paul newbold Statistical Quality Control -- Montgomery

Planned Learning Activities and Teaching Methods

1- Class Lecturing , 2- Lectures on applications , 3- Presentations of Case Studies, 4- Discussion and analysis of case studies

Assessment Methods

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

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)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 2 28 Preparations before/after weekly lectures 14 3 42 Preparation for midterm exam 1 10 10 Preparation for final exam 1 10 10 Preparing assignments 14 4 56 Final 1 2 2 Midterm 1 2 2 TOTAL WORKLOAD (hours) 150

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 LO.1 3 4 3 LO.2 3 4 3 LO.3 3 4 4 3 LO.4 3 4 3 LO.5 3 4 3 LO.6 3 4 3