COURSE UNIT TITLE

: R STATISTICAL PROGRAMMING LANGUAGE

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IST 2050 R STATISTICAL PROGRAMMING LANGUAGE COMPULSORY 2 2 0 6

Offered By

Statistics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR ENGIN YILDIZTEPE

Offered to

Statistics
Statistics(Evening)

Course Objective

The goal of this course is to introduce undergraduate students to the statistical programming and graphics using R.

Learning Outcomes of the Course Unit

1   Describing the syntax of the R programming language
2   Using different data types properly
3   Using functions for data visualization and graphics
4   Using control structures
5   Writing functions for statistical methods
6   Doing fundamental statistical analysis using the R functions

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 The R environment, Data structures, vector, logical vector, factor
2 Data structures, matrix, data.frame, list, array
3 Data Import and export, data manipulations
4 Built-in functions, Math functions, descriptive statistics, String manipulation functions
5 Base graphics functions
6 Probability and distributions
7 Random data, density and distribution functions
8 Control structures; Conditional statements, Selection and matching
9 Control structures; Loops, Efficient calculations; vectorized computations, The apply family
10 Programming with functions, User-written functions
11 Programming with functions; Scope, variables and arguments
12 Advanced graphics
13 Advanced graphics ; ggplot2 package
14 R Applications

Recomended or Required Reading

Textbook(s):
1. Braun W.J., Murdoch D.J., A First Course in Statistical Programming with R, Cambridge, 2009.
2. Matloff N., The Art of R programming, 2011.
Supplementary Book(s):
1. Jones, O., Maillardet, R., & Robinson, A. (2014). Introduction to scientific programming and simulation using R. CRC Press.
2. Kabacoff, R. (2011). R in Action: Data Analysis and Graphics with R. Manning Publications Co.

Planned Learning Activities and Teaching Methods

Lecture, examples and PC laboratory exercises.

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 (RESIT) MTE * 0.50 + RST * 0.50


Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of exams.

Language of Instruction

English

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 https://fen.deu.edu.tr/

Contact Details for the Lecturer(s)

DEU Faculty of Sciences Department of Statistics
e-mail: engin.yildiztepe@deu.edu.tr
Phone:+90 232 301 86 04

Office Hours

Thursday 15.30-16.30

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
Web Search and Library Research 7 3 21
Preparation for final exam 1 30 30
Preparation for midterm exam 1 25 25
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.1554
LO.2554
LO.3554
LO.4554
LO.55454
LO.65454

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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