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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS VYA 5019 APPLIED STATISTICS COMPULSORY 3 0 0 6

Offered By

DATA MANAGEMENT AND ANALYSIS

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR LEVENT ŞENYAY

Offered to

DATA MANAGEMENT AND ANALYSIS

Course Objective

The aim of the course is to able to obtain descriptive and interpretive statistics, regression and correlation analysis methods applied in the fields of operations research, examination and interpretation of the results. Students might need in solving problems involving basic statistical methods course is designed for the application. Software and programing will be used.

Learning Outcomes of the Course Unit

1   Reveal to.the relationship between science and statistical methods 2   To be able to explain to measures of central tendency and measures of variation 3   Classify to according to the characteristics of variables 4   A data set to show graphs 5   To reveal the relationship between data 6   To be able to identify the basic concepts of the science of statistics. 7   According to the values of measures of central tendency to describe the shape of the distribution

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Basic concepts in statistics 2 Frequency tables and graphs to analyze data 3 Summary statistics: Mean, variance and standard deviation 4 Basic probability 5 Some important discrete probability distributions: binomial, hypergeometric, and Poisson distributions 6 Some important continuous probability distributions: normal and exponential distributions 7 Distributions of sample mean and sample rate 8 Interval estimation: Mean, rate and variance 9 Interval estimation: the difference between two means and two rates 10 Hypothesis testing: Mean, rate and variance 11 Hypothesis testing: the difference between two means and two rates 12 Hypothesis testing: two variance comparison 13 Regression Analysis 14 Applied cases

Recomended or Required Reading

Statistics for Business and Economics, Paul Newbold

Planned Learning Activities and Teaching Methods

Discussing, Problem solving, Lecture Method, Question-Answer Method

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 * 0.30 + STT * 0.30 + FIN* 0.40 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + STT * 0.30 + RST* 0.40 *** 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)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 3 42 Preparations before/after weekly lectures 12 2 24 Preparation for midterm exam 1 15 15 Preparation for final exam 1 15 15 Preparing assignments 10 4 40 Midterm 1 2 2 Final 1 2 2 TOTAL WORKLOAD (hours) 140

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 LO.1 1 LO.2 1 1 1 1 LO.3 1 1 1 1 LO.4 1 1 1 1 1 LO.5 1 1 1 1 1 LO.6 1 1 1 1 LO.7 1 1 1 1 1