# 统计推断

## Statistical Inference

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Coursera
• 完成时间大约为 16 个小时
• 混合难度
• 英语, 韩语, 其他

### 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

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

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

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

Week 4: Power, Bootstrapping, & Permutation Tests
We will begin looking into power, bootstrapping, and permutation tests.

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