COURSE UNIT TITLE

: INFERENTIAL STATISTICAL METHODS FOR DATA SCIENCE

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
DSM 5002 INFERENTIAL STATISTICAL METHODS 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 ÖZGÜL VUPA ÇILENGIROĞLU

Offered to

Data Science
Data Science (Non-Thesis-Evening)

Course Objective

The main objective of this course is to introduce students to some basic statistical concepts and to teach the basic statistical methods used for data analysis.

Learning Outcomes of the Course Unit

1   1. Know when and how to apply basic Statistical Inference ideas, Sampling distributions, including the Central Limit Theorem;
2   2. Appreciate the relationship between confidence intervals and tests of hypotheses and appythem using the R program.
3   3. Know to apply Hypothesis Testing about One and Two Population Parameters and apply them using the R program.
4   4. Know when and how to apply the Chi-Square Statistic to test for goodness of fit and for independence and applies it using the R program.
5   5. Know when and how to apply basic Nonparametric Statistical Tests apply them using the R program
6   6. Know to apply Analysis of Variance and applies it by using R program.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Basic Concepts of Statistical Inference
2 Sampling Distributions (Z, Chi-square, t, F), Central Limit theorem
3 Inferences Based on a Single Sample: Estimation with Confidence Interval
4 Inferences Based on Two Samples: Estimation with Confidence Interval
5 Inferences Based on a Single Sample: Test of Hypotheses Testing
6 Inferences Based on a Single Sample: Test of Hypotheses Testing(continued)
7 Inferences Based on Two Samples: Test of Hypotheses , Power of test
8 Inferences Based on Two Samples: Test of Hypotheses (continued)
9 Power of test
10 Introduction to categorical data analysis and applications of chi-squared Statistic
11 Analysis of Variance: Comparing More Than Two Means Introduction to Simple Linear Regression
12 Nonparametric Statistics(Sign Test, Run Test, Wilcoxon signed-rank test)
13 Nonparametric Statistics(Mann Withney test, Kruskal-Wallis test)
14 Friedman test, Mc Namer test

Recomended or Required Reading

1. Michael W. Trosset, An Introduction to Statistical Inference and Applications with R (Chapman & Hall/CRC Texts in Statistical Science) 1st Edition, ISBN-13: 978-1584889472, ISBN-10: 1584889470.
2.. James T. McClave , Feank H. Dietrich,II, and Terry Sincich, Statistics 9th Edition, Prentice Hall, ISBN 0-13-471542-X.
3.Öniz Toktamış, Semra Türkan ,R Programı ile Temel Istatistiksel Yöntemler,Seçkin Yayıncılık, ISBN: 9789750244681.

Planned Learning Activities and Teaching Methods

The course consists of lecture and class discussion

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG ASSIGNMENT
2 PRS PRESENTATION
3 FCG FINAL COURSE GRADE ASG * 0.50 + PRS * 0.50


Further Notes About Assessment Methods

None

Assessment Criteria

Assessment Methods:

Homework Assignments (50%)+Report&Presentation(50%)

Language of Instruction

Turkish

Course Policies and Rules

Reading the related parts of the course material each week, attending the course and participating in class discussions are the requirements of the course. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy. You can find the undergraduate policy at www.fef.deu.edu.tr

Contact Details for the Lecturer(s)

Prof.Dr.Özlem EGE ORUÇ
DEU. Faculty Sciences Department of Statistics B113
e-mail: ozlem.ege@deu.edu.tr
Tel: 0232 3018558
Dr.Öğretim ÜyesiÖzgül VUPA ÇILENGIROĞLU
DEU. Faculty Sciences Department of Statistics B151/2
e-mail: ozgul.vupa@deu.edu.tr
Tel: 0232 3018562

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 14 5 70
Preparing report 1 28 28
Preparing assignments 5 10 50
Web Search and Library Research 1 10 10
Final 0 0 0
TOTAL WORKLOAD (hours) 200

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7
LO.15255
LO.252553
LO.352553
LO.452553
LO.552553
LO.652553

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

HOME / ABOUT US / DEGREE PROGRAMMES / GENERAL INFORMATION FOR STUDENTS / INTERNATIONAL RELATIONS