统计推断

Statistical Inference

2037 次查看
约翰霍普金斯大学
Coursera
  • 完成时间大约为 16 个小时
  • 混合难度
  • 英语, 韩语, 其他
注:本课程由Coursera和Linkshare共同提供,因开课平台的各种因素变化,以上开课日期仅供参考

你将学到什么

Describe variability, distributions, limits, and confidence intervals

Make informed data analysis decisions

Understand the process of drawing conclusions about populations or scientific truths from data

Use p-values, confidence intervals, and permutation tests

课程概况

Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. Furthermore, there are broad theories (frequentists, Bayesian, likelihood, design based, …) and numerous complexities (missing data, observed and unobserved confounding, biases) for performing inference. A practitioner can often be left in a debilitating maze of techniques, philosophies and nuance. This course presents the fundamentals of inference in a practical approach for getting things done. After taking this course, students will understand the broad directions of statistical inference and use this information for making informed choices in analyzing data.

课程大纲

周1
完成时间为 18 小时
Week 1: Probability & Expected Values
This week, we'll focus on the fundamentals including probability, random variables, expectations and more.
10 个视频 (总计 64 分钟), 11 个阅读材料, 6 个测验

周2
完成时间为 11 小时
Week 2: Variability, Distribution, & Asymptotics
We're going to tackle variability, distributions, limits, and confidence intervals.
10 个视频 (总计 76 分钟), 4 个阅读材料, 4 个测验

周3
完成时间为 11 小时
Week: Intervals, Testing, & Pvalues
We will be taking a look at intervals, testing, and pvalues in this lesson.
11 个视频 (总计 83 分钟), 5 个阅读材料, 4 个测验

周4
完成时间为 13 小时
Week 4: Power, Bootstrapping, & Permutation Tests
We will begin looking into power, bootstrapping, and permutation tests.

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