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Inference for Numerical Data in R

高级技能水平
更新时间 2020年9月
In this course you'll learn techniques for performing statistical inference on numerical data.
免费开始课程
RProbability & Statistics
4小时
15 视频
49 道练习
3,650 XP
14,237
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课程描述

In this course, you'll learn how to use statistical techniques to make inferences and estimations using numerical data. This course uses two approaches to these common tasks. The first makes use of bootstrapping and permutation to create resample based tests and confidence intervals. The second uses theoretical results and the t-distribution to achieve the same result. You'll learn how (and when) to perform a t-test, create a confidence interval, and do an ANOVA!

先决条件

Foundations of Inference in R
1

Bootstrapping for estimating a parameter

In this chapter you'll use bootstrapping techniques to estimate a single parameter from a numerical distribution.
开始章节
2

Introducing the t-distribution

In this chapter you'll use Central Limit Theorem based techniques to estimate a single parameter from a numerical distribution. You will do this using the t-distribution.
开始章节
3

Inference for difference in two parameters

In this chapter you'll extend what you have learned so far to use both simulation and CLT based techniques for inference on the difference between two parameters from two independent numerical distributions.
开始章节
Inference for Numerical Data in R
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