4.3
557 个评分

## 课程概述

Inferential statistics are concerned with making inferences based on relations found in the sample, to relations in the population. Inferential statistics help us decide, for example, whether the differences between groups that we see in our data are strong enough to provide support for our hypothesis that group differences exist in general, in the entire population. We will start by considering the basic principles of significance testing: the sampling and test statistic distribution, p-value, significance level, power and type I and type II errors. Then we will consider a large number of statistical tests and techniques that help us make inferences for different types of data and different types of research designs. For each individual statistical test we will consider how it works, for what data and design it is appropriate and how results should be interpreted. You will also learn how to perform these tests using freely available software. For those who are already familiar with statistical testing: We will look at z-tests for 1 and 2 proportions, McNemar's test for dependent proportions, t-tests for 1 mean (paired differences) and 2 means, the Chi-square test for independence, Fisher’s exact test, simple regression (linear and exponential) and multiple regression (linear and logistic), one way and factorial analysis of variance, and non-parametric tests (Wilcoxon, Kruskal-Wallis, sign test, signed-rank test, runs test)....

## 热门审阅

MN

Jul 24, 2020

Feeling blessed to perform this course . It was truly an amazing experience for me to go though this course .Learned bunch of theories with their mathematical example.Thanks to the instructors.

ND

Feb 12, 2018

Incredibly dense (which they warn you about) so the lecutres fly over so much important info it's hard to keep track of even with a strong focus. A very good overview though.

## 76 - 推论统计 的 100 个评论（共 148 个）

Nov 30, 2020

Very rigorous but rewarding course

Jun 2, 2020

A very good course, I gained a lot!

Jul 26, 2018

Wow! This course was challenging!

Nov 2, 2020

I love this coursera very much.

Jun 6, 2018

I love it. Thank you very much!

Jun 19, 2017

Challenging and great course..

May 9, 2016

Quite difficult but amazing!

Jul 9, 2018

Useful and understandable.

Mar 31, 2016

Easy to understand.

Jun 16, 2021

good knowledge

Jan 23, 2022

Good Learning

Jan 15, 2017

Great content

Mar 6, 2016

great course

Sep 19, 2020

very useful

Dec 18, 2020

Very good

Sep 19, 2020

thank you

Sep 3, 2020

excellent

Sep 3, 2020

excellent

Sep 3, 2020

excellent

Aug 7, 2018

wonderful

Jul 26, 2016

Thanks

Sep 12, 2021

best

Sep 8, 2021

good

Oct 21, 2020

good

Jun 22, 2020

good