# 學生對 阿姆斯特丹大学 提供的 推论统计 的評價和反饋

4.3
490 個評分
143 條評論

## 課程概述

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)....

## 熱門審閱

MN
2020年7月24日

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
2018年2月12日

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 個評論（共 138 個）

2018年7月26日

Wow! This course was challenging!

2020年11月2日

I love this coursera very much.

2018年6月6日

I love it. Thank you very much!

2017年6月19日

Challenging and great course..

2016年5月9日

Quite difficult but amazing!

2018年7月9日

Useful and understandable.

2016年3月31日

Easy to understand.

2021年6月16日

good knowledge

2017年1月15日

Great content

2016年3月6日

great course

2020年9月19日

very useful

2020年12月18日

Very good

2020年9月19日

thank you

2020年9月3日

excellent

2020年9月3日

excellent

2020年9月3日

excellent

2018年8月7日

wonderful

2016年7月26日

Thanks

2020年10月21日

good

2020年6月22日

good

2020年6月7日

good

2020年5月31日

good

2020年7月6日

As the name suggests, this course delivers by teaching you the basics of inferential statistics - that is, conclusions based on samples. Definitely the most challenging course in the Methods and Statistics in Social Sciences specialization, and the most important takeaways are: 1) a beginner's look into programming with R and most importantly 2) a guide in understanding which test to use under each specific circumstance.

The only thing I think this course is missing is more preparation throughout the lectures, as sometimes the example exercises aren't enough (maybe add pop questions throughout each lecture, as it was done with Quantitative Methods, would be a good idea). This lack of extra preparation throughout the lectures makes the quizzes at the end of each week more difficult because you have to do extra research through other sources to fully understand the topics.

2020年10月28日

The theoretical background into the different methods of statistical analysis, and most of the examples, were quite well done and easy to follow. I was hoping the R-lab assignments would require more work; for example: to show how to enter in a line of code (like the R-lab assignments did) and then give a second (similar) example that would reinforce how to use R properly).

Overall, I think the course is a worth-while one for students who are looking to review inferential statistics for use in the future (like I was).

2017年8月31日

While the first course Basic Statistic was really thorough with step-by-step explainations, Inferential Statistics, near the end of the course sometimes rushed through some explanations. Therefor I sometimes needed extra literature to understand the calculations. Still, I highly recommend this course!