1583 - 抽樣調查
Survey Sampling
教育目標 Course Target
The course aims to equip the students with sampling techniques, including sampling designs, derivation of expected values, variances, and the estimated variances of the estimators based on sampling designs. It is expected that the students have sufficient knowledge to design survey and analyze survey data.
This course will cover the following topics:
1. the simple random sampling (with/without replacement)
2. the stratified random sampling (the optimum allocation)
3. the poststratified estimator
4. the ratio estimator
5. cluster sampling (one-stage and two-stage, systematic sampling)
6. sampling with unequal probability (probability proportional to size (PPS) without replacement)
7. Horvitz–Thompson estimator.
The course aims to equip the students with sampling techniques, including sampling designs, derivation of expected values, variations, and the estimated variations of the estimators based on sampling designs. It is expected that the students have sufficient knowledge to design survey and analyze survey data.
This course will cover the following topics:
1. the simple random sampling (with/without replacement)
2. the stratified random sampling (the optimum allocation)
3. the poststratetified estimator
4. the ratio estimator
5. cluster sampling (one-stage and two-stage, systematic sampling)
6. sampling with unequal probability (probability proportional to size (PPS) without replacement)
7. Horvitz–Thompson estimator.
課程概述 Course Description
Sampling is widely used in the modern world. The statistical offices of many nations have sample surveys conducted on topics of interest such as unemployment, size of labor force etc.. Furthermore, sample surveys are often conducted by company on topics of the behavior of consumers.
Sampling design determines the precision of the estimates. Thus, the way a sample is drawn is as important as the mathematical form of the estimator. Sample design consists of both a sample selection plan and an estimation procedure. In this course, we shall first define population, sampling units (primary, secondary, etc.); then introduce many sampling schemes, such as simple random sampling (with or without replacement), stratified sampling (optimum allocation of sampling units to various strata), multistage sampling (e.g. two-stage stratified cluster sampling), systematic sampling, double sampling, and sampling with unequal probabilities (with or without replacement). We shall also introduce ratio estimator, regression estimator, and poststratification estimators.
Finally, we shall derive the variances of the proposed estimators and the estimators of their variances. For estimating the variance of the estimators, the topics of Jackknife method and bootstrap method are also included in this course.
Sampling is widely used in the modern world. The statistical offices of many nations have sample surveys conducted on topics of interest such as unemployment, size of labor force etc.. Further, sample surveys are often conducted by company on topics of the behavior of consumers.
Sampling design determines the precision of the estimates. Thus, the way a sample is drawn is as important as the mathematical form of the estimator. Sample design consists of both a sample selection plan and an estimation procedure. In this course, we shall first define population, sampling units (primary, secondary, etc.); then introduce many sampling schemes, such as simple random sampling (with or without replacement), stratified sampling (optimum allocation of sampling units to various strata), multistage sampling (e.g. two-stage stratified cluster sampling), systematic sampling, double sampling, and sampling with unequal probability (with or without replacement). We shall also introduce ratio estimator, regression estimator, and poststratification estimators.
Finally, we shall derive the variations of the proposed estimators and the estimators of their variations. For estimating the variation of the estimators, the topics of Jackknife method and bootstrap method are also included in this course.
參考書目 Reference Books
1. Sampling Methods for Applied Research by Peter Tryfors, John Wiley and Sons, Inc.
1. Sampling Methods for Applied Research by Peter Tryfors, John Wiley and Sons, Inc.
評分方式 Grading
評分項目 Grading Method |
配分比例 Percentage |
說明 Description |
---|---|---|
midterm midterm |
50 | |
final Final |
50 |
授課大綱 Course Plan
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相似課程 Related Courses
課程代碼 Course Code |
課程名稱 Course Name |
授課教師 Instructor |
時間地點 Time & Room |
學分 Credits |
操作 Actions |
---|---|---|---|---|---|
必修-1580
|
統計系2A 黃愉閔 | 四/6,7,8[M121] | 3-0 | 詳細資訊 Details |
課程資訊 Course Information
基本資料 Basic Information
- 課程代碼 Course Code: 1583
- 學分 Credit: 3-0
-
上課時間 Course Time:Wednesday/2,Friday/1,2[M117]
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授課教師 Teacher:沈葆聖
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修課班級 Class:統計系2B
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選課備註 Memo:人工加選,曾修習統計學下期
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