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. Altuğ ÖZDEN

Prof. Cemal ATICI

Prof. Ferit ÇOBANOĞLU

Prof. Gökhan ÇINAR

Prof. Göksel ARMAĞAN

Prof. Renan TUNALIOĞLU

Lec. Halil İbrahim YILMAZ

Lec. Sıdıka BOZKIRAN YILMAZ

Statistics For Agricultural Economics

Course Code	: TE411
Course Type	: Required
Couse Group	: First Cycle (Bachelor's Degree)
Education Language	: Turkish
Work Placement	: N/A

Theory	: 2
Prt.	: 2
Credit	: 3
Lab	: 0
ECTS	: 4

Objectives of the Course

To teach employing statistics methods on solution of the problems that are within the scope of agricultural economics

Course Content

A linear regression model with a single explanatory variable, multiple linear regression model with more explanatory variables, nonparametric tests, indexes

Name of Lecturer(s)

Learning Outcomes

1.	Ability to explain the fundamental statistical concepts (central tendency, measures of dispersion, probability, sampling) and theoretical principles required to describe data in the field of agricultural economics.
2.	Design surveys and experiments to collect data from agricultural enterprises or markets, and conduct field research processes by correctly selecting sampling methods.
3.	Ability to select and apply appropriate statistical analysis methods, including hypothesis testing, analysis of variance (ANOVA), correlation, and regression, to solve complex agricultural-economic problems.
4.	Ability to effectively utilize modern software (including SPSS, R, Excel, Stata, etc.) and information technologies to process big data encountered during statistical analysis processes.
5.	Ability to accurately interpret the obtained statistical analysis results under scientific constraints, and to present them both in writing as a technical report and orally in accordance with ethical principles

Recommended or Required Reading

1.	SERPER Özer, Uygulamalı İstatistik, Filiz Kitabevi, İstanbul, 1986
2.	KARAGÖZ, Yalçın. SPSS 23 ve AMOS 23 uygulamalı istatistiksel analizler. Nobel Akademik Yayıncılık, 2016.

Weekly Detailed Course Contents

Week 1 - Theoretical

Calculation of estimators in regression models, assumptions of linear regression model, usefulness of the model, correlation, coefficient of determination

Week 2 - Theoretical

Multiple linear regression model with more explanatory variables, solution of multiple linear regression models, usefulness of estimators, usefulness of the model

Week 3 - Theoretical

Nonparametric tests, sign test, small sample sizes, large sample sizes

Week 4 - Theoretical

Mann Whitney test, Kruskal Wallis test, Spearman’s rank correlation

Week 5 - Theoretical

Simple indexes, price indexes, quantity index, value index

Week 6 - Theoretical

Chain index, total price index, total quantity index

Week 7 - Theoretical

Laspeyres price index, Paasche price index, Fisher Ideal price index,

Week 8 - Theoretical

Price deflator, concepts of real price and current price

Week 9 - Theoretical

Measurement of price volatility

Week 10 - Theoretical

Formal and equation forms of supply and demand equations

Week 11 - Theoretical

Case study: Investigation of food safety conception with statistical approaches

Week 12 - Theoretical

Case study: Analysis of possible effects of climate change on agricultural sector

Week 13 - Theoretical

Case study: Identification of food safety, and defining some critical approaches in order to determine key role of agricultural production

Week 14 - Theoretical

Indexes; simple indexes, price index, quantity index, chain index, compound indexes, laspeyres price index, paasche price index, fisher ideal price index, laspeyres quantity index, paasche quantity index, price deflator

Assessment Methods and Criteria

Type of Assessment	Count	Percent
Attending Lectures	1	%10
Presentation	1	%10
Midterm Examination	1	%20
Final Examination	1	%60

Workload Calculation

Activities	Count	Preparation	Time	Total Work Load (hours)
Lecture - Theory	14	1	2	42
Lecture - Practice	14	1	2	42
Presentation	1	2	1	3
Midterm Examination	1	5	1	6
Final Examination	1	10	1	11
TOTAL WORKLOAD (hours)				104

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	PÇ-11
OÇ-1	5	4		2	4		1	3		1	1
OÇ-2	4	4	2	2	5	1	2	3	2	3	2
OÇ-3	5	5	1	3	5		2	3	1	3	2
OÇ-4	4	4	1	5	5		1	4	1	3	1
OÇ-5	4	5		3	5	1	5	3	4	3	2