▶Japanese
Post to SNS
- Home
- > School of Engineering
- > Undergraduate major in Industrial Engineering and Economics
- > Statistics for Industrial Engineering and Economics
- School of Science
-
School of Engineering
- Undergraduate major in Mechanical Engineering
- Undergraduate major in Systems and Control Engineering
- Undergraduate major in Electrical and Electronic Engineering
- Undergraduate major in Information and Communications Engineering
- Undergraduate major in Industrial Engineering and Economics
- Common courses
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
- School of Environment and Society
- 工学院，物質理工学院，環境・社会理工学院共通科目
- Liberal arts and basic science courses
- First-Year Courses
- School of Science
- School of Engineering
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
-
School of Environment and Society
- Department of Architecture and Building Engineering
- Department of Civil and Environmental Engineering
- Department of Transdisciplinary Science and Engineering
- Department of Social and Human Sciences
- Department of Innovation Science
- Graduate major in Technology and Innovation Management
- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- Undergraduate major in Industrial Engineering and Economics
- Instructor(s)
- Miyakawa Masami Suzuki Sadami
- Class Format
- Lecture / Exercise
- Media-enhanced courses
- Day/Period(Room No.)
- Tue1-2(W934) Fri1-2(W934)
- Group
- -
- Course number
- IEE.A205
- Credits
- 2
- Academic year
- 2019
- Offered quarter
- 2Q
- Syllabus updated
- 2019/4/10
- Lecture notes updated
- 2019/7/5
- Language used
- Japanese
- Access Index
-
Course description and aims
This course focuses on probability theory and statistics with an emphasis on solving problems by quantitative analysis in industrial engineering. Topics in probability include discrete and continuous random variables, probability distributions, the law of large numbers, and the central limit theorem. Topics in statistics include sample mean and variance, estimating distributions (point estimation and confidence intervals), hypotheses testing (t-test, Chi-square test, F-test and analysis of variance), correlation, and regression with some example in our everyday life problems.
This course intends to learn statistical way of thinking and apply statistical methodology and tools to industrial engineering and everyday life problems.
Student learning outcomes
By the end of this course, students will be able to:
(1) Understand the basic concepts of probability, random variables, probability distribution, parameter estimation and hypotheses testing.
(2) Compute and interpret basic statistics using numerical and graphical techniques.
(3) Use statistical methodology and tools in the engineering problem-solving process.
(4) Apply statistical way of thinking to industrial engineering and everyday life problems.
Keywords
point estimation, interval estimation, hypotheses testing, t-test, Chi-square test, F-test (ANOVA; analysis of variance), Multiple regression analysis
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | Communication skills | ✔ Critical thinking skills | ✔ Practical and/or problem-solving skills |
Class flow
Give a lecture and give some exercise problems. Solutions for the exercise problems are also reviewed.
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | Mean and Variance | Understand basic statistics |
| Class 2 | Random Variables and Probability Distributions | Understand about random variables and probability distributions |
| Class 3 | Estimating Parameters | Calculate estimating parameters and confidence intervals/confidence level |
| Class 4 | Estimation of the Mean | Estimation of the mean based on normal distribution |
| Class 5 | Estimation of the Variance | Estimation of basic statistics utilizing various distributions |
| Class 6 | Test for the Mean | Testing hypotheses about parameters of normal distribution and t-distribution |
| Class 7 | Test for the Variance | Testing hypotheses about parameters of Chi-square distribution and F-distribution |
| Class 8 | Chi-Squared Goodness-of-fit Test | Chi-Squared Goodness-of-fit Test and contingency tables |
| Class 9 | One-way ANOVA (analysis of variance) | Testing the equality of three or more means at one time by using variance |
| Class 10 | Two-way ANOVA (analysis of variance) | Understand the main effects of two independent variables and interaction effect between them |
| Class 11 | Maximum Likelihood Estimation | Understand Maximum Likelihood Estimation |
| Class 12 | Distributions of Statistics and Sum of Squares | Understand various distributions and calculate sum of squares |
| Class 13 | Determination of testing methods | Understand how to determine the testing methods |
| Class 14 | Least Squares Method | Calculate parameters using least squares methods |
| Class 15 | Multiple Regression Analysis | Modeling and calculating with multiple regression analysis |
Textbook(s)
Nothing in particular. Provide handouts when needed.
Reference books, course materials, etc.
Miyakawa, Masami. Statistical methodology. Tokyo: Kyoritsu Shuppan; ISBN-13: 978-4320016132. (Japanese)
Assessment criteria and methods
Final exam and exercise problems.
Related courses
- IEE.A204 ： Probability for Industrial Engineering and Economics
- IEE.A331 ： OR and Modeling
- IEE.C302 ： Quality Management
Prerequisites (i.e., required knowledge, skills, courses, etc.)
Students must have successfully completed "Probability for Industrial Engineering and Economics" or have equivalent knowledge.
