Information Package / Course Catalogue - Adnan Menderes University

General Information Unit Staff Academic Information Programme Outcomes Course Structure Diagram Contact Information

Person Responsible for Information Package

Prof. Mustafa KESEN

Assoc. Prof. Beyza ERER

Assoc. Prof. Didem TEZSÜRÜCÜ COŞANSU

Assoc. Prof. Funda ODUNCUOĞLU

Lec. Derya GÜL ÖZTÜRK

Computer Applied Statistics

Course Code	: İK311
Course Type	: Area Elective
Couse Group	: First Cycle (Bachelor's Degree)
Education Language	: Turkish
Work Placement	: N/A

Theory	: 3
Prt.	: 0
Credit	: 3
Lab	: 0
ECTS	: 6

Objectives of the Course

Students should use forecasting techniques as regression, time series analysis and should determine relationship between variables.

Course Content

Basic probability, statistical probability, descriptive statistics, inferential statistics, hypothesis testing, linear correlation, dealing with subjects such as regression and analysis of variance using SPSS, Excel and R software...

Name of Lecturer(s)

Learning Outcomes

1.	Students can make prediction through variable/variables.
2.	Students can learn through previous values.
3.	Students will know SPSS.
4.	Students can learn the relationship between variables.
5.	Students make parameter estimation.
6.	Students can learn the basic concepts of statistics.

Recommended or Required Reading

1.	Moore, D. S., McCabe, G. P., & Craig, B. A. (2009). Introduction to the Practice of Statistics (Vol. 4). New York: WH Freeman.
2.	Verzani, J. (2004). Using R for introductory statistics. Chapman and Hall/CRC.

Weekly Detailed Course Contents

Week 1 - Theoretical

Introduction and Basic Statistical Concepts

Week 2 - Theoretical

Data Visualisation and Graphics

Week 3 - Theoretical

Measures of Central Tendency and Dispersion

Week 4 - Theoretical

Probability Distributions

Week 5 - Theoretical

Probability Theory and Sampling Distributions

Week 6 - Theoretical

Statistical Estimation and Confidence Intervals

Week 7 - Theoretical

Hypothesis Testing

Week 8 - Theoretical

Multiple Regression and Correlation Analysis

Week 9 - Theoretical

Anova (Analysis of Variance)

Week 10 - Theoretical

Nonparametric Tests

Week 11 - Theoretical

Use of Statistical Software I

Week 12 - Theoretical

Use of Statistical Software II

Week 13 - Theoretical

Introduction to Statistical Modelling and Machine Learning

Week 14 - Theoretical

Criticism of Statistical Applications and Future Perspectives

Assessment Methods and Criteria

Type of Assessment	Count	Percent
Midterm Examination	1	%40
Final Examination	1	%60

Workload Calculation

Activities	Count	Preparation	Time	Total Work Load (hours)
Lecture - Theory	13	2	3	65
Individual Work	13	0	3	39
Midterm Examination	1	20	1	21
Final Examination	1	25	1	26
TOTAL WORKLOAD (hours)				151

Contribution of Learning Outcomes to Programme Outcomes

	PÇ-1	PÇ-2	PÇ-3	PÇ-4	PÇ-5	PÇ-6	PÇ-7	PÇ-8	PÇ-9	PÇ-10
OÇ-1	4	4	4	4	4	4	4	4	4	4
OÇ-2	5	5	5	5	5	5	5	5	5	5
OÇ-3	5	5	5	5	5	5	5	5	5	5
OÇ-4	4	4	4	4	4	4	5	5	5	4
OÇ-5	5	5	5	5	5	5	5	5	5	5
OÇ-6	4	4	4	4	4	4	4	4	4	4