資料分析與應用
Data analysis and applications
| 節 | 週五 |
|---|---|
3 10:10–11:00 | 資料分析與應用 YR103（陽明） 2 節連堂 |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
This course offers a comprehensive introduction to data analysis with a strong emphasis on real-world biomedical and clinical applications. Designed specifically for students in biomedical informatics, it equips learners with the analytical skills needed to extract meaningful insights from complex health and biological datasets. The course begins with foundational data analysis techniques to uncover relationships and associations within biomedical data, followed by statistical visualization methods — including summary statistics and graphical plots — to effectively communicate findings. Students will then explore inferential statistics for both numeric and categorical data, with examples drawn from clinical trials, genomics, and electronic health records. The latter half of the course covers data exploration, preprocessing, and regression modeling, with an emphasis on translational applications in precision medicine and public health. Combining lectures with hands-on programming exercises, this course prepares students to confidently tackle data-driven challenges in biomedical research. Assessment includes analytic exercises, a course project, and a final implementation project in which students apply learned techniques to a biomedical dataset of their choice.
Students are expected to have a basic understanding of statistics and familiarity with at least one programming language (such as Python or R) prior to enrolling in this course.
無備註
This course employs a combination of lectures and hands-on programming demonstrations to reinforce analytical concepts. Students are encouraged to actively participate in in-class exercises using their own laptops. Course materials, assignments, and announcements will be distributed via the course management system (e.g., E3). A teaching assistant (TA) will be available for weekly office hours to provide guidance on assignments and projects. Recommended references include course handouts, online tutorials, and access to biomedical databases such as PubMed, NCBI, and UCI Machine Learning Repository for dataset exploration.
Analytic Exercises / Homework 25% Class Participation 10% e-Learning Course Material Completion 15% Course Project 15% Final Implementation Project 35%
教師未提供此項資料
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction to data analysis 2026-09-11(五) 時數：[2026-09-11]蘇家玉(2.00) |
| 第 2 週 | Data and variable properties 2026-09-18(五) 時數：[2026-09-18]蘇家玉(2.00) |
| 第 3 週 | Data conversion and normalization 2026-09-25(五) 時數：[2026-09-25]蘇家玉(2.00) |
| 第 4 週 | Queries: sorting and filtering 2026-10-02(五) 時數：[2026-10-02]蘇家玉(2.00) |
| 第 5 週 | Table decomposition and combination 2026-10-09(五) 時數：[2026-10-09]蘇家玉(2.00) |
| 第 6 週 | Summary statistics 2026-10-16(五) 時數：[2026-10-16]蘇家玉(2.00) |
| 第 7 週 | Generating statistical plots 2026-10-23(五) 時數：[2026-10-23]蘇家玉(2.00) |
| 第 8 週 | Data visualization 2026-10-30(五) 時數：[2026-10-30]蘇家玉(2.00) |
| 第 9 週 | Inference for numeric data: t-test and confidence intervals 2026-11-06(五) 時數：[2026-11-06]蘇家玉(2.00) |
| 第 10 週 | Inference for categorical data: chi-square test 2026-11-13(五) 時數：[2026-11-13]蘇家玉(2.00) |
| 第 11 週 | Relationship analysis: ANOVA and correlation analysis 2026-11-20(五) 時數：[2026-11-20]蘇家玉(2.00) |
| 第 12 週 | Linear regression 2026-11-27(五) 時數：[2026-11-27]蘇家玉(2.00) |
| 第 13 週 | Sampling, exploration and modification 2026-12-04(五) 時數：[2026-12-04]蘇家玉(2.00) |
| 第 14 週 | Data analysis evaluation techniques 2026-12-11(五) 時數：[2026-12-11]蘇家玉(2.00) |
| 第 15 週 | Data analysis project implementation 2026-12-18(五) 時數：[2026-12-18]蘇家玉(2.00) |
| 第 16 週 | Data analysis project demonstration 2026-12-25(五) 時數：[2026-12-25]蘇家玉(2.00) |
| 第 17 週 | Data analysis project report writing (Flexible supplement learning) 2027-01-01(五) 時數：[2027-01-01]蘇家玉(2.00) |
| 第 18 週 | Data analysis project mutual evaluation (Flexible supplement learning) 2027-01-08(五) 時數：[2027-01-08]蘇家玉(2.00) |
Book's name: Data Handling and Analysis (Fundamentals of Biomedical Science) Author: Andrew Blann Publisher: Oxford University Press; 2nd Edition
- 地點
- Shou-Ren Building 3F Discussion Room
- 時間
- Thursday morning 9am-12pm
- 聯絡方式
- By appointment