TÜRKÇE
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Information
| Unit | FACULTY OF AGRICULTURE |
| FIELD CROPS PR. | |
| Code | TBP138 |
| Name | Statistics |
| Term | 2018-2019 Academic Year |
| Semester | 2. Semester |
| Duration (T+A) | 2-2 (T-A) (17 Week) |
| ECTS | 3 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Lisans Dersi |
| Type | Normal |
| Label | C Compulsory |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. ZEYNEL CEBECİ |
| Course Instructor |
Prof. Dr. ZEYNEL CEBECİ
(Bahar)
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
This course aims to teach to interprete results of a variety of statistical techniques from both descriptive and inferential statistics; to understand the fundamental concepts in statistics including sampling, experimentation, variability, distribution, association, causation, estimation, confidence, hypothesis testing, and significance; to critically review and analyze statistical arguments.
Course Content
Topics include both descriptive and inferential statistics: variables; graphical analysis of one or more qualitative and quantitative variables; numerical summaries to measure characteristics such as the center of a distribution, variation in a distribution, and symmetry or skewness in a distribution; random sampling; the normal distribution; the Central Limit Theorem; one and two sample hypothesis tests and confidence intervals involving means and proportions; one-way analysis of variance; the chi-square goodness-of-fit test; the chi-square test concerning independence in a two-way contingency table; Pearson correlation and testing for significance with simple linear regression.
Course Precondition
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Defines fundamental statistical concepts and terms. |
| LO02 | Designs, implements, and summarizes data from simple experimental plans. |
| LO03 | Explains probability theory and performs basic probability calculations. |
| LO04 | Applies and interprets basic inferential statistical data analysis. |
| LO05 | Explains hypothesis testing and analyzes two-sample data comparisons. |
| LO06 | Calculates and interprets descriptive statistics for univariate data. |
| LO07 | Analyzes and interprets relationships between two variables. |
| LO08 | Conducts one-way analysis of variance (ANOVA) and evaluates the results. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | - | Has knowledge about agricultural engineering as well as agronomy and breeding of field crops. | 2 |
| PLO02 | - | Determines and solves the problems related to agricultural engineering as well as agronomy and breeding of field crops. | 2 |
| PLO03 | - | Graduates gain abilty to synthetize the basic concepts related to the field crops. | 0 |
| PLO04 | - | Rrecognises problems related to agricultural engineering,makes decisions and takes initiative to solve the problems. | 1 |
| PLO05 | - | Gains knowledge about sustainable agriculture, protection of environment and natural sources, biodiversity and conservation of genetic sources. | 0 |
| PLO06 | - | Gains ability to optimize the plant production by sustainable use of natural resources. | 2 |
| PLO07 | - | Learns basic principles of breeding and biotechnology of field crops. | 1 |
| PLO08 | - | Chooses and uses modern technical equipments for the agricultural engineering applications as well as for the applications in the agronomy and breeding of field crops. | 2 |
| PLO09 | - | Gains ability to establish suitable research experiments for the purpose and the ability to interpret its results by scientific methods. | 5 |
| PLO10 | - | Works both individually and in a team. | 3 |
| PLO11 | - | Evaluates the learned knowledge by analytical and critical approach. | 5 |
| PLO12 | - | Internalizes the necessity of lifelong learning. | 4 |
| PLO13 | - | Has an effective and healthy communication in his fıeld and use communication technologies. | 3 |
| PLO14 | - | Improve themselves consistently by determining educational requirements in scientific, cultural and social areas depending on their abilities,besides their career development | 2 |
| PLO15 | - | Shows respect to job ethic. | 3 |
| PLO16 | - | Becomes competent in the legislation and management systems related to agricultural engineering. | 0 |
| PLO17 | - | Becomes proficient in doing, applying, managing and monitoring plans and projects about agricultural engineering | 3 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Introduction to statistics, Definition of terms and basic concepts, Statistical symbols, Data and Variables, Variable types | Search for learning resources on Introduction to statistics on the Internet, and reading the texts about definition and goals of statistics. | |
| 2 | Population, Samples and Sampling | Reading the relevant topic chapters from printed and/or e-books. | |
| 3 | Numerical and visual summarizing data, Frequency tables, Histograms, Charts, Type of graphics, Interpretation of distributions | Download and setup R statisctical package from The Comprehensive R Archive Network, and search for R tutorials on the Internet and download some of them | |
| 4 | Measures of central tendency, arithmetic mean, weighted mean, harmonic mean, geometric mean, truncated mean, mode, median, quartiles, quantiles and percentiles | Reading the relevant topic chapters from printed and/or e-books. | |
| 5 | Measures of variation/dispersion: Range, Variance, Standard deviation, Coefficient of variation, Skewness and Curtosis, Standard error of mean | Reading the relevant topic chapters from printed and/or e-books. | |
| 6 | Introduction to probability: Probability rules, experiment, sample space, simple event, event, complement of an event, union and intersections of events, probability of an event, conditional probabilities, independent events, mutually exclusive events and Venn diagrams | Reading the relevant topic chapters from printed and/or e-books. | |
| 7 | Discrete probability distributions: Binomial distributions, Poisson distributions | Reading the relevant topic chapters from printed and/or e-books. | |
| 8 | Mid-Term Exam | Preparation for the exam | |
| 9 | Interval estimation of a population proportion and estimation of a population mean | Reading the relevant topic chapters from printed and/or e-books. | |
| 10 | Determining sample size | Rdetermining sample sizeeading the relevant topic chapters from printed and/or e-books. | |
| 11 | Null and alternative hypothesis; type I and type II errors; Tests on population meansand proportions | Reading the relevant topic chapters from printed and/or e-books. | |
| 12 | Tests about differences between the means of two populations, independent samples and matched samples, Tests about the differences in proportion. Hypothesis tests about population variances and two population variance | Reading the relevant topic chapters from printed and/or e-books. | |
| 13 | Chi-square analysis: Goodness of fit test; test of independence using contingency tables | Reading the relevant topic chapters from printed and/or e-books. | |
| 14 | Analysis of bivariate data: Estimation of correlation ve linear regression, Scatter plots | Reading the relevant topic chapters from printed and/or e-books. | |
| 15 | Introduction to one-way ANOVA | Reading the relevant topic chapters from printed and/or e-books. | |
| 16 | Term Exams | Preparation for the exam | |
| 17 | Term Exams | Preparation for the exam |
Assessment (Exam) Methods and Criteria
| Assessment Type | Midterm / Year Impact | End of Term / End of Year Impact |
|---|---|---|
| 1. Midterm Exam | 60 | 24 |
| 1. Homework | 40 | 16 |
| General Assessment | ||
| Midterm / Year Total | 100 | 40 |
| 1. Final Exam | - | 60 |
| Grand Total | - | 100 |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 2 | 28 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 3 | 42 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 4 | 4 |
| Final Exam | 1 | 12 | 12 |
| Total Workload (Hour) | 86 | ||
| Total Workload / 25 (h) | 3,44 | ||
| ECTS | 3 ECTS | ||