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| ORM1004 | Biometry | 3+0+0 | ECTS:5 | | Year / Semester | Spring Semester | | Level of Course | First Cycle | | Status | Compulsory | | Department | DEPARTMENT of FOREST ENGINEERING | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Dr. Öğr. Üyesi Serkan AKBAŞ | | Co-Lecturer | PROF. DR. Nuray MISIR, | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | To teach students basic statistical skills and find solutions in relaiton to a number of statistical promlems in forestry and other sciences |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | Define and explain basic statistical terms and rules
| 2 - 3 - 5 | | | LO - 2 : | Implement some statistical analysis in relation to data
| 2 - 3 - 5 | | | LO - 3 : | Compare independent data sets.
| 2 - 3 - 5 | | | LO - 4 : | Apply and analyze single-variable parametric and non-parametric tests
| 2 - 3 - 5 | | | LO - 5 : | Formularize statistically a real problem and solve and analyze it
| 2 - 3 - 5 | | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome | | |
| Introduction to statistics, definition of statistical terms, classification of data, descriptive statistics, probability, permutation anda combination, theoretical distributions, sampling methods, parametric and non-parametric tests, analysis of variance, correlation and regression analyses, sampling design.
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Introduction to biometry | | | Week 2 | Classification of data | | | Week 3 | Central tendency measures (Arithmetic mean, geometric mean, mode and median) | | | Week 4 | Variance, standard deviation, standard error, percent error, coefficient of variation | | | Week 5 | Theoretical Distributions (Binom and Poisson) | | | Week 6 | Normal Distribution | | | Week 7 | Hypothesis Tests (One-sample t-test,Independent-samples t-test) | | | Week 8 | Hypothesis Tests (Paired-samples t-test) | | | Week 9 | Mid-term exam | | | Week 10 | Chi-Squre Tests (Independence and homogenity tests) | | | Week 11 | Appropriateness to normal distribution | | | Week 12 | One-way Anova | | | Week 13 | Correlation Analysis, Simple Linear Regression analysis | | | Week 14 | Multiple Regression analysis | | | Week 15 | Sampling techniques | | | Week 16 | End-of-term exam | | | |
| 1 | Kalıpsız, A. İstatistiksel Yöntemler, İ.Ü. Yayınları, No 3522, İstanbul | | | 2 | Batu, F. 1995; Uygulamalı İstatistik Yöntemler, KTÜ Yayınları, No 179, Trabzon | | | 3 | Sümbüloğlu, K. ve Sümbüloğlu, V. 2009; Biyoistatistik, Hatipoğlu, Ankara | | | |
| 1 | Özdamar, K. 2003; Paket Programlar İle İstatistiksel Veri Analizleri, Kaan Kitabevi, Ankara | | | 2 | Freeze, F. 1984; statistics for Land Managers, Paeony Press, ISBN 0 946941 009, Scotland | | | 3 | Akalp, T. 2016. İstatistik Yöntemler, İstanbul Üniversitesi Orman fakültesi Yayın No: 511, ISBN 978-605-07-0597-3. | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | 24.04.2023 | 0,45 | 50 | | End-of-term exam | 16 | 19.06.2023 | 1 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 3 | 15 | 45 | | Sınıf dışı çalışma | 1 | 16 | 16 | | Arasınav için hazırlık | 2 | 8 | 16 | | Arasınav | 1.5 | 1 | 1.5 | | Dönem sonu sınavı için hazırlık | 4 | 14 | 56 | | Dönem sonu sınavı | 1.5 | 1 | 1.5 | | Total work load | | | 136 |
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