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A Classroom Approach to Illustrate Transformation and Bootstrap Confidence Interval Techniques Using the Poisson Distribution

机译:使用泊松分布来说明转换和自举置信区间技术的课堂方法

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The Poisson distribution is here used to illustrate transformation and bootstrap techniques in order to construct a confidence interval for a mean. A comparison is made between the derived intervals and the Wald? and score confidence intervals. The discussion takes place in a classroom, where the teacher and the students have previously discussed and evaluated the Wald and score confidence intervals. While step by step? interactively getting acquainted? with new techniques,? the students will learn about the effects of e.g. bias and asymmetry and ways of dealing with such phenomena. The primary purpose of this teacher-student communication is therefore not to find the? best possible interval estimator for this particular case, but rather to provide a study displaying a teacher and her/his students interacting with each other in an efficient and rewarding way. The teacher has a strategy of encouraging the students to take initiatives. This is accomplished by providing the necessary background of the problem and some underlying theory after which the students are confronted with questions and problem solving. From this the learning process starts. The teacher has to be flexible according to how the students react. The students are supposed to have studied mathematical statistics for at least two semesters.
机译:泊松分布在这里用于说明变换和自动启动技术,以便为平均值构造置信区间。在衍生的间隔和沃尔德之间进行比较?并得分置信区间。讨论发生在课堂上,教师和学生们之前已经讨论过沃尔德和评分置信区间。逐步一步?交互式熟悉?用新技术,?学生将学习例如e的效果。偏见和不对称和处理此类现象的方式。因此,这位师生沟通的主要目的是不是找到?对于这种特殊情况,最佳的间隔估算器,而是提供一项关于展示教师和她/他的学生以有效和有益的方式互动的研究。老师有一种鼓励学生采取举措的策略。这是通过提供问题的必要背景和一些潜在的理论来实现,之后学生面临问题和解决问题。从这个学习过程开始。教师必须根据学生的反应方式灵活。学生应该研究至少两个学期的数学统计数据。

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