課程名稱 |
環境統計與風險評估 ENVIRONMENTAL STATISTICS AND RISK ASSESSMENT |
開課學期 |
98-1 |
授課對象 |
生物資源暨農學院 生物環境系統工程學系 |
授課教師 |
鄭克聲 |
課號 |
BSE5108 |
課程識別碼 |
622EU4400 |
班次 |
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學分 |
3 |
全/半年 |
半年 |
必/選修 |
選修 |
上課時間 |
星期五2,3,4(9:10~12:10) |
上課地點 |
生工202 |
備註 |
本課程以英語授課。與任秀慧合開 總人數上限:30人 |
課程網頁 |
http://homepage.ntu.edu.tw/~ritayam/envstat.htm |
課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
課程大綱
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課程概述 |
Overview
Environmental statistics is simply the application of statistical methods to problems concerning the environment. It is a special field of statistics based on probability and statistics. It is often conceived to be a set of tools environmental scientists used to derive quantitative conclusion from their data obtained from systems in various fields including hydrology, ecology, geology, chemistry, epidemiology, oceanography, and atmospheric modelling. Though this field is relatively young, the relevant data analysis methods have been widely used for environmental research and practical activities such as:
monitoring air or water quality;
environmental monitoring near a hazardous or solid waste site;
risk assessment to determine whether a potentially contaminated/ physically degraded area needs to be cleaned up/ restored, and if so, how much;
assessing whether a previously contaminated/ physically degraded area has been cleaned up/ restored according to some specific criteria; and
risk analysis for flood mapping.
In spite of the usefulness and wide applicability of environmental statistics for data analysis in environmental management, misusing of statistical methods will always lead to misinterpretation of the situation and inappropriate decision making. To avoid such problem, it is important to understand the fundamental theories underlying the statistical methods commonly used for environmental data analysis, why and how to apply them on different types of data, and how to interpret the statistics results without bias.
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課程目標 |
This course will aim to:
Introduce design of sampling program and statistics methods for environmental data and risk assessment in health aspects at an elementary to intermediate level, with the emphasis on practical applications of statistical methods and models to experimental and monitoring data.
Cover with topics including data quality objectives (DQO) process and data quality assessment, sampling design, hypothesis testing and concepts of probability, summary statistics, linear models, nonparametric statistics methods for environmental change detection, geostatistics, Monte Carlo simulation and risk assessment. Each statistical method will be taught with both fundamental theories and detailed illustration of each method with wide range of real-world examples.
Describe and develop environmental statistical models through both lectures and practical sessions. Students will develop their own spreadsheet models (as a mini project), and will be introduced to models used in practice.
Introduce the concepts of interpretation and decision making in environmental field based on the results of statistical analysis.
Discuss the concepts and practices involved in health risk assessment, and give examples of how to perform probabilistic risk assessment.
Enable students to learn highly practical techniques for sampling design, statistical analysis and modelling of environmental data, risk assessment which are essential skills for academic research and practical application on data handling and problem investigation for environmental related career.
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課程要求 |
Grad policy
Homeworks: 60%
Midterm exam: 20%
Project report and presentation: 20%
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預期每週課後學習時數 |
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Office Hours |
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指定閱讀 |
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參考書目 |
1.Probability Concepts in Engineering Planning and Design. John Wiley and Sons, 1975.
2.Modeling Hydrologic Change – Statistical Methods. Lewis Publishers, 2003.
3.Applied Multivariate Techniques. Wiley, 1996.
4.Environmental Statistics –Methods and Applications. Wiley, 2004.
5.Statistical Methods for Detection and Quantification of Environmental Contamination. Wiley, 2001.
6.Statistics for Environmental Science and Management. Chapman and Hall/CRC, 2001.
7.Statistics for the Environment 2 – Water Related Issues. Wiley, 1994.
8.Environmental and Health Risk Assessment and Management. Springer, 2006. |
評量方式 (僅供參考) |
No. |
項目 |
百分比 |
說明 |
1. |
Group project |
20% |
Presentation and report |
2. |
Mid-term examination |
20% |
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3. |
Homework |
60% |
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週次 |
日期 |
單元主題 |
Week 1 |
9/19 |
1. Course overview; 2. Basic statistics |
Week 2 |
9/26 |
1. Normal distribution;
2. Inferential statistics |
Week 3 |
10/03 |
Linear model I |
Week 4 |
10/10 |
*No lecture. University holiday. |
Week 5 |
10/17 |
Linear model II |
Week 6 |
10/24 |
Sampling design |
Week 7 |
10/31 |
Non-parametric statistics methods for environmental change detection |
Week 8 |
11/07 |
Geostatistics (spatial statistics) I |
Week 9 |
11/14 |
Midterm Exam |
Week 10 |
11/21 |
Geostatistics (spatial statistics) II |
Week 11 |
11/28 |
Environmentric models |
Week 12 |
12/05 |
Monte Carlo simulation I |
Week 13 |
12/12 |
Monte Carlo simulation II |
Week 14 |
12/19 |
Health risk assessment I |
Week 15 |
12/26 |
Health risk assessment II |
Week 16 |
1/02 |
Student presentation |
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