TÜRKÇE
ENGLISH
Information
| Code | IG219 |
| Name | Statistics |
| Semester | 3. Semester |
| Duration (T+A) | 2-2 (T-A) (17 Week) |
| ECTS | 5 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Lisans Dersi |
| Type | Uygulamalı Ders |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Doç. Dr. SELMA TOKER KUTAY |
Course Goal
The aim of this course is to provide students with a general skill in collecting, analyzing and interpreting statistical data.
Course Content
The topics of this course include sampling distribution, statistical estimation, hypothesis testing, simple and multiple linear regression, experimental design and applications of these topics to industrial systems engineering.
Course Precondition
None
Resources
Probability and Statistics, Murray R. Spiegel, John J. Schiller, Jr., R. Alu Srinivasan, Schaums Outlines, 2nd Ed., 2013.
Notes
Lecture Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Students who can successfully complete this course; will be able to analyze data using graphical and numerical methods. |
| LO02 | Understand the basics of statistical decision making. |
| LO03 | Will be able to use basic tools to analyze and model experimental relationships between variables. |
| LO04 | Will be able to analyze data via computer programme. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Have sufficient knowledge in the fields of basic sciences (mathematics / science) and food engineering and the ability to use theoretical and applied knowledge in these areas in complex engineering problems. | 2 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Identifies, defines and solves complex engineering problems in applications in the fields of food engineering and technology. | 3 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Gains the ability to apply a complex system or process related to food products and production components using modern design methods under certain constraints and conditions. | |
| PLO04 | Bilgi - Kuramsal, Olgusal | Choosing and using modern technical tools necessary for analysis and solution of complex problems encountered in food engineering and technology applications; For this purpose, he/she uses information technologies. | |
| PLO05 | Bilgi - Kuramsal, Olgusal | Gaining laboratory skills for the analysis and solution of complex problems in the field of food engineering, designing an experiment, conducting an experiment, collecting data, analyzing and interpreting the results. | |
| PLO06 | Bilgi - Kuramsal, Olgusal | Takes responsibility individually and as a team member to solve problems encountered in food engineering applications. | |
| PLO07 | Bilgi - Kuramsal, Olgusal | Gains the ability to communicate verbally and in writing in Turkish / English related to the field of food engineering, to write reports, to prepare design and production reports, to present effectively and to use communication technologies. | |
| PLO08 | Bilgi - Kuramsal, Olgusal | Recognizing the necessity of lifelong learning and constantly improving himself/herself in the field of food engineering. | |
| PLO09 | Bilgi - Kuramsal, Olgusal | Gains the awareness of food legislation and management systems and professional ethics. | |
| PLO10 | Bilgi - Kuramsal, Olgusal | Using the knowledge of project design and management, he/she attempts to develop and realize new ideas about food engineering applications; have information about sustainability. | |
| PLO11 | Bilgi - Kuramsal, Olgusal | Has awareness about the effects and legal consequences of engineering practices related to food safety and quality on consumer health and environmental safety within the framework of national and international legal regulations. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Descriptive Statistics | Lecture Notes | Öğretim Yöntemleri: Anlatım |
| 2 | Sample distributions and point estimation | Lecture Notes | Öğretim Yöntemleri: Anlatım |
| 3 | Sample distributions and point estimation-2 | Lecture Notes | Öğretim Yöntemleri: Anlatım |
| 4 | Sample distributions and point estimation-3 | Lecture Notes | Öğretim Yöntemleri: Anlatım |
| 5 | Confidence Interval Estimation for Single Sample | Lecture Notes | Öğretim Yöntemleri: Anlatım |
| 6 | Confidence Interval Estimation for Single Sample-2 | Lecture Notes | Öğretim Yöntemleri: Anlatım |
| 7 | Confidence Interval Estimation for Two Samples | Lecture Notes | Öğretim Yöntemleri: Anlatım |
| 8 | Mid-Term Exam | Lecture Notes | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Hypothesis Tests for Single Sample | Lecture Notes | Öğretim Yöntemleri: Anlatım |
| 10 | Hypothesis Tests for Single Sample-2 | Lecture Notes | Öğretim Yöntemleri: Anlatım |
| 11 | Hypothesis Testing for Two Samples | Lecture Notes | Öğretim Yöntemleri: Anlatım |
| 12 | Hypothesis Testing for Two Samples-2 | Lecture Notes | Öğretim Yöntemleri: Anlatım |
| 13 | Simple Linear Regression and Correlation | Lecture Notes | Öğretim Yöntemleri: Anlatım |
| 14 | Multiple Linear Regression and Correlation and Excel Applications | Lecture Notes | Öğretim Yöntemleri: Anlatım |
| 15 | Multiple Linear Regression and Correlation and Excel Applications-2 | Lecture Notes | Öğretim Yöntemleri: Anlatım |
| 16 | Term Exams | Lecture Notes | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Term Exams | Lecture Notes | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 4 | 56 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 3 | 42 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 1 | 3 | 3 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 8 | 8 |
| Final Exam | 1 | 16 | 16 |
| Total Workload (Hour) | 125 | ||
| Total Workload / 25 (h) | 5,00 | ||
| ECTS | 5 ECTS | ||