COURSE UNIT TITLE

: STATISTICAL PROGRAMMING LANGUAGES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IST 3154 STATISTICAL PROGRAMMING LANGUAGES ELECTIVE 3 0 0 5

Offered By

Statistics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASISTANT PROFESSOR ENGIN YILDIZTEPE

Offered to

Statistics
Statistics(Evening)

Course Objective

This course provides students with knowledge of programming for basic calculations and statistical methods, data manipulation and graphic construction with using R.

Learning Outcomes of the Course Unit

1   Describing properties of 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
7   Building a statistical simulation study

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, installation, using help
2 Calculation with R, Operators
3 Data types, vector, matrix
4 Array, list and data.frame
5 Control structures
6 Loop structures
7 Functions and writing function
8 Midterm exam
9 Functions and writing function
10 Using statistical functions in R
11 Probability distributions, Generating random variables
12 Data visualization and graphics
13 Data import, export functions in R
14 Using R Packages/ Simulation studies with R

Recomended or Required Reading

Textbook(s):
Braun W.J., Murdoch D.J., A First Course in Statistical Programming with R, Cambridge, 2009.
Supplementary Book(s):
1. Spector P., Data Manipulation with R, Springer, 2008.
2. Crawley M.J. The R Book, Wiley, 2007.
3. Kabacoff R.I., R in Action, Manning, 2011.
Materials: Lecture slides, R Manuals.

Planned Learning Activities and Teaching Methods

Lecture, homework assignments, examples and PC laboratory exercises.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FINS FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + ASG * 0.20 + FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + ASG * 0.20 + RST * 0.50

Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of exams and homeworks.

Language of Instruction

English

Course Policies and Rules

Student responsibilities:
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)

DEU Faculty of Sciences Department of Statistics
e-mail: engin.yildiztepe@deu.edu.tr
Phone:+90 232 301 86 04
e-mail: firat.ozdemir@deu.edu.tr
Phone:+90 232 301 85 52

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparations before/after weekly lectures 12 1 12
Preparation for midterm exam 1 21 21
Preparation for final exam 1 30 30
Preparing assignments 2 5 10
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 116

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14
LO.155
LO.255
LO.355
LO.455
LO.53545
LO.63545
LO.73545