Iğdır University Lifelong Learning Programme

Description of Individual Course Units

Course Unit Code	Course Unit Title	Type of Course Unit	Year of Study	Semester	Number of ECTS Credits
TBİ-23-189	Data MInIng TechnIques In AgrIcultural Research	Elective	1	1	6

Level of Course Unit

Second Cycle

Objectives of the Course

• to teach basic data mining statistical analyses techniques useful for agricultural research • to teach performing data mining techniques using agricultural data • to teach how to interpret the results of data mining techniques

Name of Lecturer(s)

Doç. Dr. Melekşen AKIN

Learning Outcomes

1	learn main data mining techniques
2	learn how to perform data mining techniques using R software
3	learn how to interpret the outputs of the data mining techniques

Mode of Delivery

Daytime Class

Prerequisites and co-requisities

None

Recommended Optional Programme Components

None

Course Contents

•Data Mining Techniques in Agricultural Research London

Weekly Detailed Course Contents

Week	Theoretical	Practice	Laboratory
1	Introduction to CHAID data mining technique
2	Performing CHAID algorith
3	Interpreting CHAID algorithm outputs
4	Introduction to CART data mining technique
5	Performing CART algorithm using R software
6	Interpreting CART algorithm outputs
7	Introduction to exhaustive CHAID data mining technique
8	Performing exhaustive CHAID algorithm using R software
9	Interpreting exhaustive CHAID algorithm outputs
10	Introduction to MARS data mining algorithm
11	Performing MARS single response algorithm using R software
12	Interpreting MARS single response algorithm outputs
13	Performing MARS multiple response algorithm using R software
14	Interpreting MARS multiple response algorithm outputs m using R software

Recommended or Required Reading

• Nisbet R, Elder J & Miner G (2009) Handbook of statistical analysis and data mining applications. Academic Press, London

Planned Learning Activities and Teaching Methods

Assessment Methods and Criteria

Term (or Year) Learning Activities	Quantity	Weight
Midterm Examination	1	100
SUM		100
End Of Term (or Year) Learning Activities	Quantity	Weight
Final Examination	1	100
SUM		100
Term (or Year) Learning Activities		40
End Of Term (or Year) Learning Activities		60
SUM		100

Language of Instruction

Work Placement(s)

None

Workload Calculation

Activities	Number	Time (hours)	Total Work Load (hours)
Midterm Examination	1	30	30
Final Examination	1	30	30
Discussion	1	30	30
Writing Paper	1	30	30
Self Study	1	30	30
Report	1	30	30
TOTAL WORKLOAD (hours)			180

Contribution of Learning Outcomes to Programme Outcomes

	PO 1	PO 2	PO 3	PO 4	PO 5	PO 6
LO1
LO2
LO3

* Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High