IST302

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

Course Term (Course Semester)	Teaching and Learning Methods							Credits
Course Term (Course Semester)	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)