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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EMT 3025 NON-PARAMETRIC STATISTICS ELECTIVE 3 0 0 5

Offered By

Econometrics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR ISTEM KÖYMEN

Offered to

Econometrics Econometrics (Evening)

Course Objective

Statistical data analysis techniques used in cases where the data are normally distributed non-parametric tests to teach.

Learning Outcomes of the Course Unit

1   To be able to plan how to test noparametric trials 2   To be able to analyze obtained from count data (cross-tables) 3   To be able to test the data conformity any distribution 4   To be able to test the sample is random or not 5   To be able to analyze the data (one sample, two samples and more than two samples) which are not normal and interpret the results

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 One Population Test: Sign Test 2 One Population Test: Wilcoxon Sign-Run Test 3 Two Population Comprasion Test(independent samples): Wilcoxon Run Test, Two Population Comprasion Test(paired samples): Sign Test, 4 Two Population Comprasion Test: Wilcoxon Sign-Run Test 5 Kruskall Wallis H Test, Friedman F Test 6 Spearman Rank Correlation Test 7 Run s Test 8 Mid-term 9 Mid-term 10 Independence and Homogeneity Tests 11 Comprasion of more than two proportions 12 Goodness of fits test ( chi-square ) 13 Goodness of fits test ( chi- square ) 14 Goodness of fits test ( kolmogorov smirnof test )

Recomended or Required Reading

1. McClave ve Benson, Statistics For Business and Economics. 2. Ross, Introduction to Probability and Statistics for Engineer and Scientists.

Planned Learning Activities and Teaching Methods

This course will be presented using class lectures, class discussions, overhead projections, and demonstrations.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 MTEG MIDTERM GRADE MTEG * 1 3 FIN FINAL EXAM 4 FCGR FINAL COURSE GRADE MTEG * 0.40 + FIN * 0.60 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTEG * 0.40 + RST * 0.60

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 12 3 36 Preparations before/after weekly lectures 12 2 24 Preparation for midterm exam 1 25 25 Preparation for final exam 1 28 28 Midterm 1 1 1 Final 1 1 1 TOTAL WORKLOAD (hours) 115

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 LO.1 1 LO.2 1 LO.3 1 LO.4 1 LO.5 1