FACULTY OF ENGINEERING
Department of Food Engineering
MATH 280 | Course Introduction and Application Information
| Course Name |
Introduction to Probability and Statistics
|
|
Code
|
Semester
|
Theory
(hour/week) |
Application/Lab
(hour/week) |
Local Credits
|
ECTS
|
|
MATH 280
|
Fall/Spring
|
2
|
2
|
3
|
6
|
| Prerequisites |
|
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| Course Language |
English
|
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| Course Type |
Elective
|
|||||||
| Course Level |
First Cycle
|
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| Mode of Delivery | - | |||||||
| Teaching Methods and Techniques of the Course | Lecture / Presentation | |||||||
| Course Coordinator | ||||||||
| Course Lecturer(s) | ||||||||
| Assistant(s) | ||||||||
| Course Objectives | To provide the fundamental concepts of Probability and Statistics with applications of business and economic problems. Fundamental statistical methods and applications are presented especially for students who want to specialize in areas where data analysis and results need to be interpreted. |
| Learning Outcomes |
The students who succeeded in this course;
|
| Course Description | This course investigate probability, discrete and continuous probability distributions. Also, provides constructing the sampling distributions, confidence interval estimation and Hypothesis tests of one and two populations. |
|
|
Core Courses | |
| Major Area Courses | ||
| Supportive Courses | ||
| Media and Management Skills Courses | ||
| Transferable Skill Courses |
WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES
| Week | Subjects | Related Preparation |
| 1 | Describing data: graphical | Newbold P., Carlson W.L., Thorne B., “Describing data: graphical”, chap 1 Statistics for Business and Economics, 10th edition (United States of America: Pearson, 2022), 25-62. |
| 2 | Describing data: numerical | Newbold P., Carlson W.L., Thorne B., “Describing data: numerical”, chap 2 Statistics for Business and Economics, 10th edition (United States of America: Pearson, 2022), 63-96. |
| 3 | Probability | Newbold P., Carlson W.L., Thorne B., “Probability”, chap 3 Statistics for Business and Economics, 10th edition (United States of America: Pearson, 2022), 97-149. |
| 4 | Probability | Newbold P., Carlson W.L., Thorne B., “Probability”, chap 3 in Statistics for Business and Economics, 10th edition (United States of America: Pearson, 2022), 97-149. |
| 5 | Probability | Newbold P., Carlson W.L., Thorne B., “Probability”, chap 3 in Statistics for Business and Economics, 10th edition (United States of America: Pearson, 2022), 97-149. |
| 6 | Discrete Random Variable, Bernoulli and Binomial Probability Distributions, Jointly Distributed Discrete Random Variables | Newbold P., Carlson W.L., Thorne B., “Discrete random variables and Probability Distributions”, chap 4 Statistics for Business and Economics, 10th edition (United States of America: Pearson, 2022), 150-200. |
| 7 | Continuous Random Variable, Normal Distribution, Jointly Distributed Continuous Random Variables | Newbold P., Carlson W.L., Thorne B., “Continuous random variables and Probability Distributions”, chap 5 Statistics for Business and Economics, 10th edition (United States of America: Pearson, 2022), 201-247. |
| 8 | Sampling, Sampling Distribution of Sample Mean and Sampling Distribution of Sample Proportion | Newbold P., Carlson W.L., Thorne B., “Sampling and sampling distributions”, chap 6 Statistics for Business and Economics, 10th edition (United States of America: Pearson, 2022), 248-287. |
| 9 | Midterm | |
| 10 | Estimation: Confidence Interval for Single Population Mean, Confidence Interval for Single Population Proportion and Determining Sample Size | Newbold P., Carlson W.L., Thorne B., “Estimation: single population”, chap 7 Statistics for Business and Economics, 10th edition (United States of America: Pearson, 2022), 288-331. |
| 11 | Estimation: Confidence Interval for Two Population Means, Confidence Interval for Two Population Proportions | Newbold P., Carlson W.L., Thorne B., “Estimation: additional topics”, chap 8 Statistics for Business and Economics, 10th edition (United States of America: Pearson, 2022), 332-349. |
| 12 | Hypothesis Testing: Single Population Mean and Single Population Proportion | Newbold P., Carlson W.L., Thorne B., “Hypothesis testing: single polulation”, chap 9 Statistics for Business and Economics, 10th edition (United States of America: Pearson, 2022), 350-388. |
| 13 | Hypothesis Testing: Two Population Means and Two Population Proportions | Newbold P., Carlson W.L., Thorne B., “Hypothesis testing: additional topics”, chap 10 Statistics for Business and Economics, 10th edition (United States of America: Pearson, 2022), 389-420. |
| 14 | Semester Review | |
| 15 | Semester Review | |
| 16 | Final exam |
| Course Notes/Textbooks | Newbold P., Carlson W.L., Thorne B., Statistics for Business and Economics, 10th edition (Pearson, 2022), ISBN-13:978-1292436845 |
| Suggested Readings/Materials | Lind D., Marchal S., Statistical Techniques in Business & Economics, 17th edition (McGraw-Hill, 2017), ISBN-13: 978-1259666360 |
EVALUATION SYSTEM
| Semester Activities | Number | Weigthing |
| Participation | ||
| Laboratory / Application | ||
| Field Work | ||
| Quizzes / Studio Critiques |
2
|
20
|
| Portfolio | ||
| Homework / Assignments | ||
| Presentation / Jury | ||
| Project | ||
| Seminar / Workshop | ||
| Oral Exams | ||
| Midterm |
1
|
30
|
| Final Exam |
1
|
50
|
| Total |
| Weighting of Semester Activities on the Final Grade |
3
|
50
|
| Weighting of End-of-Semester Activities on the Final Grade |
1
|
50
|
| Total |
ECTS / WORKLOAD TABLE
| Semester Activities | Number | Duration (Hours) | Workload |
|---|---|---|---|
| Theoretical Course Hours (Including exam week: 16 x total hours) |
16
|
2
|
32
|
| Laboratory / Application Hours (Including exam week: '.16.' x total hours) |
16
|
2
|
32
|
| Study Hours Out of Class |
14
|
2
|
28
|
| Field Work |
0
|
||
| Quizzes / Studio Critiques |
2
|
10
|
20
|
| Portfolio |
0
|
||
| Homework / Assignments |
0
|
||
| Presentation / Jury |
0
|
||
| Project |
0
|
||
| Seminar / Workshop |
0
|
||
| Oral Exam |
0
|
||
| Midterms |
1
|
28
|
28
|
| Final Exam |
1
|
40
|
40
|
| Total |
180
|
COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP
|
#
|
Program Competencies/Outcomes |
* Contribution Level
|
||||
|
1
|
2
|
3
|
4
|
5
|
||
| 1 | Being able to transfer knowledge and skills acquired in mathematics and science into engineering, | |||||
| 2 | Being able to identify and solve problem areas related to Food Engineering, | |||||
| 3 | Being able to design projects and production systems related to Food Engineering, gather data, analyze them and utilize their outcomes in practice, | |||||
| 4 | Having the necessary skills to develop and use novel technologies and equipment in the field of food engineering, |
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| 5 | Being able to take part actively in team work, express his/her ideas freely, make efficient decisions as well as working individually, |
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| 6 | Being able to follow universal developments and innovations, improve himself/herself continuously and have an awareness to enhance the quality, |
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| 7 | Having professional and ethical awareness, |
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| 8 | Being aware of universal issues such as environment, health, occupational safety in solving problems related to Food Engineering, | |||||
| 9 | Being able to apply entrepreneurship, innovativeness and sustainability in the profession, |
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| 10 | Being able to use software programs in Food Engineering and have the necessary knowledge and skills to use information and communication technologies that may be encountered in practice (European Computer Driving License, Advanced Level), |
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| 11 | Being able to gather information about food engineering and communicate with colleagues using a foreign language ("European Language Portfolio Global Scale", Level B1) |
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| 12 | Being able to speak a second foreign language at intermediate level. |
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| 13 | Being able to relate the knowledge accumulated during the history of humanity to the field of expertise |
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*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest
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