Statistics

This subject introduces the basic elements of statistical modelling, computation and data analysis. It is an entry point to further study of both mathematical and applied statistics, as well as broader data science. Students will develop the ability to fit statistical models to data, estimate parameters of interest and test hypotheses. Both classical and Bayesian approaches will be covered. The importance of the underlying mathematical theory of statistics and the use of modern statistical software will be emphasised. Concepts covered include: descriptive statistics, random sample, statistical inference, point estimation, interval estimation, properties of estimators, maximum likelihood, confidence intervals, hypothesis testing and Bayesian inference. Applications covered include: exploratory data analysis, inference for samples from univariate distributions, simple linear regression, correlation, goodness-of-fit tests and analysis of variance.

本课程介绍统计建模、计算和数据分析的基本要素。它是进一步学习数学和应用统计学以及更广泛数据科学的入门。学生将培养将统计模型拟合到数据、估计感兴趣参数和检验假设的能力。课程将涵盖经典方法和贝叶斯方法。将强调统计学基础数学理论的重要性以及现代统计软件的使用。涵盖的概念包括：描述性统计、随机样本、统计推断、点估计、区间估计、估计量的性质、最大似然估计。

• 1Demonstrate an understanding of the basic ideas of estimation and hypothesis testing;
• 2Carry out many standard statistical procedures using a statistical computing package;
• 3Fit statistical models to data by both estimating and testing hypotheses about model parameters.