Python在概率论与数理统计教学中的应用——以区间估计与假设检验为例
The Application of Python in the Teaching of Probability Theory and Mathematical Statistics—Interval Estimation and Hypothesis Testing as Examples

Python是一种广泛使用的解释型、高级和通用的编程语言。Python作为最受欢迎的语言之一，在中学和大学教学中被广泛应用。概率论与数理统计是大学数学的必修课程，其中有许多重要的实践内容。但在大部分教材中，解决相关实际问题大多使用R、Matlab或者SPSS软件进行教学。实际上，利用Python能方便的实现概率论与数理统计中的相关计算，能有效的加深学生对理论知识的理解，提高学生的综合运用能力。本文以区间估计和假设检验两个重要知识点为例，对如何在概率论与数理统计教学过程中引入Python工具，使用怎样的正确代码来解决实际问题。python在概率论与数理统计教学中应用能够提高学生的学习兴趣并进行更深入的研究，对相关课程的教学提供更有效的方法，在学生学习专业相关知识的同时提高编程能力，具有一定的实用意义。
Python is a widely used interpreted, high-level, and general-purpose programming language. As one of the most popular languages, Python is widely used in secondary school and university teaching. Probability theory and mathematical statistics are compulsory courses in university mathematics, and there are many important practical contents in them. However, in most textbooks, most of the practical problems are solved using R, Matlab or SPSS software. In fact, the use of Python can easily realize the relevant calculations in probability theory and mathematical statistics, which can effectively deepen students’ understanding of theoretical knowledge and improve students’ comprehensive application ability. Taking the two important knowledge points of interval estimation and hypothesis testing as examples, this paper explains how to introduce Python tools in the teaching process of probability theory and mathematical statistics, and what kind of correct code to use to solve practical problems. The application of python in the teaching of probability theory and mathematical statistics can improve students’ learning interest and conduct more indepth research, provide more effective methods for the teaching of related courses, and improve programming ability while students learn professional knowledge, which has certain practical significance.