COURSE UNIT TITLE

: PROBABILITY AND STATISTICS FOR DATA SCIENCE

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
DSM 5001 PROBABILITY AND STATISTICS FOR DATA SCIENCE ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR TUĞBA YILDIZ

Offered to

Data Science
Data Science - (Non-Thesis-Evening)

Course Objective

The objective of this course is to construct the basis of probability and statistics for analyzing big data sets.

Learning Outcomes of the Course Unit

1   Use numerical and graphical tools for summarizing data sets
2   Calculate descriptive statistics
3   Calculate probabilities
4   Calculate probability, expected value and moments for discrete and continuous random variables by probability functions
5   Use sampling distributions and apply central limit theorem
6   Construct confidence intervals and test statistical hypothesis for various parameters
7   Calculate covariance and correlation coefficient

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Fundamental Elements of Statistics, Types of Data
2 Numerical and Graphical Methods for Describing Data
3 Fundamental Probability Concepts, Conditional Probability and Bayes Theorem
4 Discrete Random Variables, Probability Distributions, The Expected Value, Variance and Moments
5 Continuous Random Variables, Probability Distribution Functions, The Expected Value, Variance and Moments
6 Special Discrete Distributions
7 Special Continuous Distributions
8 Midterm Exam
9 Sampling Distributions and The Central Limit Theorem
10 Interval Estimation for Population Mean, Proportion and Variance
11 The Elements of a Hypothesis Test, Test of Hypothesis About a Population Mean, Proportion and Variance
12 Comparing Two Population Means, Comparing Two Population Proportions
13 Comparing Two Population Variances
14 Covariance and Correlation

Recomended or Required Reading

Main textbooks:
1. Ross, S.M., Çeviri Editörleri: Çelebioğlu, S., Kasap, R. (2012). Mühendislik ve Fenciler için Olasılık ve Istatistiğe Giriş, Nobel Akademik Yayıncılık.
2. Toktamış, Ö., Türkan, S. (2017). R Programı ile Istatistiğe Giriş, Seçkin Yayıncılık.
3. Toktamış, Ö., Türkan, S. (2017). R Programı ile Temel Istatistiksel Yöntemler, Seçkin Yayıncılık.
Other materials: Lecture slides, Web sources

Planned Learning Activities and Teaching Methods

The course consists of lecture, homeworks and applications.

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 MTE * 0.50 + RST * 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of exams, homeworks and presentations.

Language of Instruction

Turkish

Course Policies and Rules

Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture and homework delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy. You can find the graduate policy at http://www.fbe.deu.edu.tr/

Contact Details for the Lecturer(s)

DEU Faculty of Science Department of Statistics
e-mail: tugba.ozkal@deu.edu.tr, senem.sahan@deu.edu.tr
phone: +90 232 301 86 02, +90 232 301 86 03

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 2 28
Tutorials 14 1 14
Preparations before/after weekly lectures 14 1 14
Preparation for midterm exam 1 40 40
Preparation for final exam 1 45 45
Preparing assignments 4 1 4
Preparing presentations 1 15 15
In-class practices 1 25 25
0
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 189

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7
LO.155555
LO.255555
LO.344444
LO.444455
LO.524244
LO.65555554
LO.74444554

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

Copyright 2015 DEÜ. BİD

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