COURSE UNIT TITLE

: NONPARAMETRIC STATISTICAL METHODS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IST 4035 NONPARAMETRIC STATISTICAL METHODS COMPULSORY 2 2 0 6

Offered By

Statistics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR SELMA GÜRLER

Offered to

Statistics
Statistics(Evening)

Course Objective

This course aims to introduce nonparametric statistical methods which are used widely. To learn basic concepts and to use nonparametric tests in place of their parametric. To make students to learn alternative methods of data analysis.

Learning Outcomes of the Course Unit

1   To apply non-parametric statistical methods to data obtained from a single sample
2   To apply non-parametric statistical methods using data obtained from two independent samples
3   To apply statistical methods to data obtained from a two dependent samples.
4   To apply statistical methods to data obtained from three or more independent samples.
5   To apply statistical methods to data obtained from three or more dependent samples.
6   To apply chi-square tests of independence and homogeneity.
7   To apply goodness of fit test.
8   To compute measures of association.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to non-parametric methods and review
2 Tests for a single location parameter; Making inferences about a location parameter: Sign Test-Wilcoxon Signed-Ranks Test, Binomial test, A runs test for randomness
3 Methods for two independent samples; Making inferences about the differences between two location parameters: Median test - Mann-Whitney Test Making inferences about the equality of two dispersion parameters: Moses Test, Mood Test
4 Methods for paired samples; Sign Test for two related samples, Wilcoxon Matched-Pairs Signed-Ranks Test, McNemar Test for two related samples
5 Chi-Square Tests for Independence and Homogeneity
6 Chi-square goodness-of-fit tests, Kolmogorov-Smirnov one-sample test, Kolmogorov-Smirnov two-sample test
7 Three or more independent samples; Extension of the Median test
8 Three or more independent samples; Kruskal-Wallis test and Multiple comparisons by ranks
9 Three or more related samples; Friedman two-way analysis of variance by rank, Multiple comparisons
10 Cochran Test for related observations, Measures of association; Spearman rank correlation coefficient
11 Measures of association; Kendall tau, Kendall coefficient of concordance W
12 Measures of association; Gamma coefficient, Cramer-V, Chi-square coefficient, Kappa
13 Permutation Test
14 Review

Recomended or Required Reading

Textbook(s):
- Daniel, W.W., (1990). 2nd Ed. Applied Nonparametric Statistics. PWS-KENT Publishing Company.
- Gamgam H., Altunkaynak B. (2012).Parametrik Olmayan Yöntemler. Seçkin Yayıncılık, 4. Baskı, Ankara.
Supplementary Book(s):
- Sheskin, D.J., (2000) Handbook of parametric and nonparametric statistical procedures 2nd Ed. Chapman & Hall.
- Kloke, J, McKean, J.W.,(2014) Nonparametric Statistical Methods Using R, Chapman & Hall/CRC

Planned Learning Activities and Teaching Methods

Lecture, class discussion, homeworks.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.40 + ASG * 0.20 + FIN * 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + ASG * 0.20 + RST * 0.40


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

Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of Homeworks and Exams

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 undergraduate policy at http://web.deu.edu.tr/fen

Contact Details for the Lecturer(s)

Dr. Engin YILDIZTEPE
DEÜ Faculty of Science
Department of Statistics
e-mail: engin.yildiztepe@deu.edu.tr
Phone: 0232 301 86 04

Office Hours

Tuesday 13.30-16.00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 2 28
Tutorials 14 2 28
Preparations before/after weekly lectures 14 1 14
Preparation for midterm exam 1 30 30
Preparation for final exam 1 30 30
Preparing assignments 2 8 16
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 150

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14
LO.135245
LO.235245
LO.335245
LO.435245
LO.535245
LO.635245
LO.735245
LO.835245

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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