2018 Applied Probability and Statistical Theory

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Academic unit or major
Undergraduate major in Electrical and Electronic Engineering
Kajikawa Kotaro  Kawano Yukio 
Class Format
Media-enhanced courses
Day/Period(Room No.)
Tue3-4(S221)  Fri3-4(S221)  
Course number
Academic year
Offered quarter
Syllabus updated
Lecture notes updated
Language used
Access Index

Course description and aims

It is vital to acquire knowledge and skills in statistics and probability in various fields related to electrical engineering and information communication engineering. By combining lectures and exercises, the course enables students to understand and learn the fundamentals of mean, variance, characteristic function, etc. in the first part (probability) and those of unbiased estimation, maximum likelihood estimation, hypothesis testing, etc. in the second part (statistics).
 The ability to derive statistically significant information will be very useful in the real world.

Student learning outcomes

Students will be able to learn how to analyze data in various fields related to electrical engineering and information communication engineering by using probablistic methods and statistical techniques. The course provides specific examples in engineering, which will give a deeper understanding. Many practical exercises and exams will enable students to acquire knowledge effectively.


Probability, Mean, Variance, Maximum likelihood estimation, Hypothesis testing

Competencies that will be developed

Specialist skills Intercultural skills Communication skills Critical thinking skills Practical and/or problem-solving skills

Class flow

To cultivate practical ability, students are given many exercise problems, which are related to a previous class and a class on the day.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Permutations Understand the Permutations
Class 2 Conditional probability Calculate conditional probability.
Class 3 Mean and variance Calculate mean and variance
Class 4 Characteristic function Understand characteristic function
Class 5 Random variable and distribution I Understand random variable and distribution
Class 6 Random variable and distribution II Understand random variable and distribution
Class 7 Random variable and distribution III Understand random variable and distribution
Class 8 Test level of understanding with exercise problems Test level of understanding for classes 1–7
Class 9 Review of the first part of the course Review the first part (probability) and understand the introduction to the second part (statistics)
Class 10 Statistical estimation Calculate several types of means
Class 11 Unbiased estimation Understand unbiased estimation
Class 12 Maximum likelihood estimation Learn how to perform maximum likelihood estimation
Class 13 Hypothesis testing Learn applications of hypothesis testing
Class 14 Stochastic process I Perform regression analysis calculation
Class 15 Stochastic process II Calculate correlation coefficient



Reference books, course materials, etc.

Watanabe, Sumio, Noboru, Murata, Probability and statistics: a bridge to information science, Corona-sha; ISBN: 9784339060775 (in Japanese)
Ogura, Hisanao, stochastic process for physics and engineering, Corona-sha; ISBN: 9784339004229, 9784339004236 (in Japanese)
Shibata, Fumiaki, Probability and statistics, Iwanami-shoten; ISBN: 9784000079778 (in Japanese)
Baba, Noriyuki, Kuchii, Shigeru, Campus seminar: statistics, mathema-shuppan, ISBN: 9784907165314 (in Japanese)

Assessment criteria and methods

Students' knowledge of probability and statistical, and their ability to apply them to problems will be assessed.
Midterm exam 40%, final exam 40%, exercise problems 20%.

Related courses

  • LAS.M101 : Calculus I / Recitation
  • LAS.M105 : Calculus II
  • EEE.M211 : Fourier Transform and Laplace Transform
  • EEE.S341 : Communication Theory (Electrical and Electronic Engineering)

Prerequisites (i.e., required knowledge, skills, courses, etc.)

Students must have successfully completed both Calculus I and Calculus II.


Contact by e-mail in advance.

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