| Summary: | 碩士 === 國立交通大學 === 管理科學系所 === 99 === As the degree of correlation between two variables is one of concern to many social science issues, thus using the sample correlation coefficient to infer population correlation coefficient is a common method. However, the decision of the optimum sample size for the entire study will save a lot of time and cost. Traditionally, the sample size determination in addition to hypothesis testing method, this research will introduce the expected interval length method and the expected interval coverage probability method. Expected interval coverage probability method is based on interval estimation, but it can adjust sample size strict and loose according to the different set coverage probability. In this dissertation, the SAS software is used to construct model, after finding the optimal sample size, we will select the sample size randomly from the two designed population, and observe the interval width and interval coverage probability composed of sample size whether consistent with our original set. The results shows: the expected interval length method will have a better simulation results only when the samples are large enough, and the expected interval coverage probability method will shows unstable when the population parameters very close to 0.
|
|---|
