Course title
バイオ統計学・アドバンスドバイオインフォマティクス   [Bio-statistics and Advanced Bioinformatics]
Course category technology speciality courses  Requirement   Credit 2 
Department   Year 24  Semester 3rd 
Course type 3rd  Course code 022152
Instructor(s)
川野 竜司, 津川 裕司   [KAWANO Ryuji, TSUGAWA Hiroshi]
Facility affiliation Faculty of Engineering Office   Email address

Course description
Although we have already learned mathematical statistics, we will learn practical biostatistical methods and bioinformatics methods that are required for actual research.
Expected Learning
When biochemical experiments are conducted, practical biostatistical methods are acquired so that they can perform statistical analysis on their own. Students will also acquire the state-of-the-art on bioinformatics.
Course schedule
Lectures, and exercises, and tests.

1st What is Biostatistics?
2nd Basics of Descriptive Statistics
3rd Basics of Estimated Statistics
4th Characteristics of sample distribution
5th Probability and Probability Distribution
6th Parametric Test
7th Nonparametric Test
8th Correlation Analysis 1
9th Correlation Analysis 2
10th Basics of Bioinformatics
11th Modeling
The T12 Regression Analysis
13th Multivariate Analysis 1
14th Multivariate Analysis 2
15th Final Exam.
Prerequisites
Related Topics: Statistics, Instrumental Analysis
Required Text(s) and Materials
はじめての統計学 鳥井恭彦著
References
Assessment/Grading
Evaluate grades with term-end test scores.The grade evaluation in this online class is premised on all attendances, and comprehensively evaluates the attitude to learn, quizzes, report, and online tests. Standard study time set by the our university is required to get the grade. The rate of evaluation is as follows: Normal score: 30%, quizzes and assignment test, and online test: 70%. Grade will be given according to the following criteria by comprehensive evaluation: S: 90 points or more, A: 80 or more and less than 90 points, B: 70 or more and less than 80 points, C: 60 or more and less than 70 points.
Message from instructor(s)
This is a class that is useful for experiments that You actually do after entering the laboratory.
Course keywords
Statistics, Analytics, Bioinformatics, Machine Learning
Office hours
Remarks 1
Remarks 2
Related URL
Lecture Language
Japanese
Language Subject
Last update
3/17/2022 4:32:45 PM