| Academic Year |
2026Year |
School/Graduate School |
School of Science |
| Lecture Code |
HB320000 |
Subject Classification |
Specialized Education |
| Subject Name |
確率・統計Ｂ |
Subject Name
（Katakana） |
カクリツ・トウケイB |
Subject Name in
English |
Probability and Mathematical Statistics B |
| Instructor |
IMORI SHINPEI |
Instructor
(Katakana) |
イモリ シンペイ |
| Campus |
Higashi-Hiroshima |
Semester/Term |
3rd-Year, Second Semester, 3Term |
| Days, Periods, and Classrooms |
(3T) Tues9-10：SCI E209, (3T) Thur9-10：SCI E210 |
| Lesson Style |
Lecture |
Lesson Style
(More Details) |
Face-to-face |
| Lecture |
| Credits |
2.0 |
Class Hours/Week |
4 |
Language of Instruction |
J
:
Japanese |
| Course Level |
3
:
Undergraduate High-Intermediate
|
| Course Area（Area） |
25
:
Science and Technology |
| Course Area（Discipline） |
01
:
Mathematics/Statistics |
| Eligible Students |
B3 |
| Keywords |
low of large numbers, central limit theorem, population and sample, estimation |
| Special Subject for Teacher Education |
|
Special Subject |
|
Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) | Mathematics
（Knowledge and Understanding）
・Acquiring knowledge and vision on advanced theories as an extension of core theory of modern mathematics. |
|---|
Class Objectives
/Class Outline |
Study theorems on convergence of ramdom variable, derivation of the distribution of statistics, and estimations |
| Class Schedule |
Lesson 1: Review of foundations of probability and mathematical statistics
Probability space, distribution of random variables, expectation, and characteristic function.
Lesson 2: Convergence of random variables (1)
Convergence in probability and low of large numbers
Lesson 3: Convergence of random variables (2)
Convergence in distribution and central limit theorem
Lesson 4: Convergence of random variables (3)
Almost sure convergence and asymptotic theories
Lesson 5: Population distribution and statistical models
Population, population distribution, and statistical models
Lesson 6: Sample mean and sample variance (1)
Lesson 7: Sample mean and sample variance (2)
Lesson 8: Order statistics
Lesson 9: Estimation (1)
Point estimation, least square method, and univariate linear regression models
Lesson 10: Estimation (2)
Unbiased estimator and likelihood method
Lesson 11: Estimation (3)
Interval estimation 1
Lesson 12: Estimation (4)
Interval estimation 2
Lesson 13: Testing hypothesis (1)
Erros in testing hypothesis
Lesson 14: Testing hypothesis (2)
Testing hypothesis
Lesson 15: Summary
Examination
The class schedule may be changed due to the progress. |
Text/Reference
Books,etc. |
「確率・統計の数学的基礎」（藤越、若木、栁原著）(in Japanese) |
PC or AV used in
Class,etc. |
Text, Microsoft Teams |
| (More Details) |
|
| Learning techniques to be incorporated |
|
Suggestions on
Preparation and
Review |
Read the text book before each lecture and solve the problems in it. |
| Requirements |
Students who take this class should understand the class contents of "Probability and Mathematical Statistics A" held in School of Science. |
| Grading Method |
Quiz and examination (and report if necessary) |
| Practical Experience |
|
| Summary of Practical Experience and Class Contents based on it |
|
| Message |
|
| Other |
|
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. |