# 98年第1學期-1385 抽樣調查 課程資訊

midterm 50
final 50

## 教育目標

In this course, we shall ﬁrst deﬁne population and sampling units (primary, secondary, etc.) so that students can understand the difference between a sample and population. Next, we shll 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). It is hoped that students can understand the differences among varying sampling schemes and know which sampling technique should be used in practice. 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. It is hoped that students know how to obtain the biases, variance and the estimatied variance of the estimators. Finally, for estimating the variance of the estimators, the topics of Jackknife method and bootstrap method are also included in this course.

## 課程概述

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.

## 參考書目

Sampling methods for applied research by Peter Tryfos; John Wiley