Information Package / Course Catalogue
Statistics
Course Code: ZT462
Course Type: Required
Couse Group: First Cycle (Bachelor's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 0
Credit: 2
Lab: 0
ECTS: 3
Objectives of the Course

The aim of this course is to provide students with a fundamental understanding of statistical concepts, data collection and sampling principles, and methods for organizing, summarizing, and interpreting data. Within the scope of the course, students are expected to develop the ability to present research data using frequency tables and graphical methods, calculate and interpret measures of central tendency and variability, understand the basic principles of probability and probability distributions, and evaluate relationships among variables through chi-square tests, correlation analysis, and simple linear regression analysis. The course also aims to equip students with the skills necessary to analyze data from a statistical perspective, interpret results accurately, and utilize statistical information effectively in scientific research and professional decision-making processes.

Course Content

1. Basic concepts of statistics, its scope, and applications in agricultural sciences. 2. Types of variables, levels of measurement, concepts of population and sample, and sampling methods. 3. Organizing data and presenting it using frequency tables and graphs. 4. Examination of measures of central tendency (arithmetic mean, median, mode, geometric mean, and harmonic mean) and measures of variability. 5. Characteristics of data distributions, and evaluation of the concepts of skewness and kurtosis. 6. Basic principles of probability theory, applications of permutations and combinations, and an introduction to probability distributions. 7. Application and interpretation of discrete probability distributions (Binomial, Hypergeometric, and Poisson) and Chi-square (?²) tests. 8. Examination and interpretation of relationships between variables using correlation and linear regression analyses.

Name of Lecturer(s)
Assoc. Prof. Onur YILMAZ
Learning Outcomes
1.Explains the basic concepts of statistics, types of variables, and the concepts of population and sample, and determines the appropriate sampling approach for research.
2.Organizes and presents data using frequency tables and graphs, and interprets it by calculating measures of central tendency and variability.
3.Explains the basic principles of probability theory; applies permutations, combinations, and basic probability distributions (Binomial, Hypergeometric, and Poisson).
4.Analyzes categorical data using chi-square (?²) tests and evaluates the results from a scientific perspective.
5.Examines relationships between variables using correlation and linear regression analyses, interprets the results, and applies them to solve research problems.
Recommended or Required Reading
1.Puskulcu, H., Ikiz, F., Eren, S. 2006. Introduction to Statistics. Baris Yayinlari. Fakulteler Kitabevi, Izmir.
2.Atil, H. 1998, Statistics (in Turkish). Published by Faculty of Agriculture of Aegean University, No.531, Bornova, İzmir.
3.Yildiz, N., Bircan, H., 2008. Applied Statistics (in Turkish). Nobel Press, Turkey. ISBN:9944770612
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to statistical reasoning, the importance of statistics in agricultural sciences, basic statistical concepts
Week 2 - Theoretical
The concept of a variable, data types (qualitative-quantitative, continuous-discrete), levels of measurement
Week 3 - Theoretical
The concepts of population and sample, sampling methods, and the rationale for sampling in agricultural research
Week 4 - Theoretical
Data organization and presentation: Frequency tables, class intervals, and graphs
Week 5 - Theoretical
Calculating the mode and median from frequency tables, as well as percentages and quartiles
Week 6 - Theoretical
Measures of central tendency: Arithmetic mean, geometric mean, and harmonic mean
Week 7 - Theoretical
Measures of variability: variance, standard deviation, coefficient of variation, and standard error
Week 8 - Theoretical
Skewness and kurtosis in data, interpreting data distributions
Week 9 - Theoretical
Basic concepts of probability theory, events, and probability calculations
Week 10 - Theoretical
Applications of permutations and combinations, an introduction to probability distributions
Week 11 - Theoretical
Discrete probability distributions: Binomial, Hypergeometric, and Poisson distributions
Week 12 - Theoretical
Chi-square (?²) tests: Tests of goodness of fit and independence
Week 13 - Theoretical
Correlation analysis: Measuring and interpreting the relationship between variables
Week 14 - Theoretical
Linear regression analysis: The regression equation, interpretation of coefficients, and agricultural applications
Assessment Methods and Criteria
Type of AssessmentCountPercent
Quiz2%10
Midterm Examination1%30
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory142256
Individual Work1112
Quiz2114
Midterm Examination1617
Final Examination1606
TOTAL WORKLOAD (hours)75
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
5
OÇ-2
5
5
OÇ-3
5
5
OÇ-4
5
5
OÇ-5
5
5
Adnan Menderes University - Information Package / Course Catalogue
2026