﻿ IST302

### IST302

Course Title Course Code Program Level
STATISTICAL SOFTWARE IST302 Statistics B.A. / B.Sc.

Course Term
(Course Semester)
Teaching and Learning Methods
Credits
Theory Practice Lab Projects/Field Work Seminars/Workshops Other Total Credits ECTS Credits
06
(Spring)
28 14 96 138 3 5

Teaching Staff
Language of Instruction Türkçe (Turkish)
Type Of Course Compulsory
Prerequisites None
Recommended Optional Programme Component
Course Objectives Object of the course is to teach the statistical software which are used in other statistics course.
Course Content Some statistical packages mostly used in statistical analysis such as R, Excel Statistical Tool Pack ve SPSS are introduced in this course.
Learning Outcomes (LO) Students will be have ability and capacity for analyze the statistical methods using statistical software in their job or working life. Students will be able to catch the some job opportunities using with their software knowledge.
Mode of Delivery Face to face
Course Outline
Week Topics
1. Week Introduction to R open system. Installing R. R commands for simple calculation.
2. Week Input and output in R. Data structures of R: vectors, matrices and lists. Basic programming with R.
3. Week Probability and distributions in R. Descriptive statistics. Graphical sub systems in R.
4. Week Single and two sample hypothesis
5. Week Regression and correlation analyses in R.
6. Week Non parametric tests and variance analysis with R
7. Week Tables and independency test with R.
8. Week Using the statistical functions in Excel. Computing descriptive statistics with Excel functions.
9. Week Installation of Excel tool pack. Simple and two sample hypothesis tests.
10. Week Statistical analysis with excel : Regression, correlation and variance analysis.
11. Week General specifications of SPSS. Data structures. Data entry and data transformations.
12. Week Creating new variables in SPSS. Survey evaluations. Table creation.
13. Week Hypothesis and tests with SPSS. Statistical analysis with SPSS. Regression, correlation and variance analysis.
14. Week Other statistical analysis with PSPS.
Assessment
 Percentage(%) Mid-term (%) 30 Quizes (%) Homeworks/Term papers (%) 20 Practice (%) Labs (%) 10 Projects/Field Work (%) Seminars/Workshops (%) Final (%) 40 Other (%) Total(%) 100
Course Book (s) and/or References 1. Peter Dalgaard (2008), Introductory Statatistics With R, Springer. 2. Dretzke Beverly J.()2005, Statistics with Microsoft Excel, Pearson, Prentice Hall 3. Joaquim P. Marques(2007), Applied Statistics Using SPSS, STATISTICA, MATLAB and R, Springer
Work Placement(s)
The Relationship between Program Qualifications (PQ) and Course Learning Outcomes (LO)