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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.

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51 - 推论统计 的 75 個評論(共 138 個)

創建者 shizhen ( J

2020年4月21日

Still like this course. If the quiz answers can be provided, that would be great!

創建者 Ivan P

2016年5月27日

Very carefully presented and organized introductory course. Well put R support.

創建者 gerardo r g

2018年12月4日

This course is very helpful for people intereted in quantitative research

創建者 Wen S

2017年11月22日

some minor flaws may exist in the test design. apart from this, all good.

創建者 Priscilla R C

2019年7月10日

It was a great class, it was difficult but it healped me learn a lot!

創建者 Santanu G

2017年6月7日

Excellent Course for Inferential Statistics and Regression Analysis

創建者 Abdirahman M

2018年2月16日

Very interesting but challenging course in Inferential Statistics.

創建者 Roberta d R B

2016年12月27日

Wonderfully useful. It has helped me to run my research analysis.

創建者 Jennifer H

2016年7月13日

Great course. Really helpful examples which were easy to follow.

創建者 Ollie G

2020年12月6日

very broad coverage of lots of statstics you'll use day to day

創建者 Marcos L L

2019年5月5日

Good course.

Very well explicate and good for learning R code.

創建者 Sonal D

2017年9月20日

course is hard you required basic understanding of statistics

創建者 june

2017年6月17日

It's an interesting course, and a little difficult to finish.

創建者 Andres F P T

2020年6月12日

The last topic on non-parametric test was not well explained

創建者 Vikram S

2017年1月28日

One of the better Statistical Inference courses out there.

創建者 Francisco J G L

2019年9月11日

Me ha hecho sufrir , estoy alegre de haber pasado OUIIIII

創建者 Nada A

2020年11月4日

this was a very challenging course but i learned a lot !

創建者 Stanislav M

2016年3月25日

Hidden jem on inferential statistics on Coursera.

創建者 Deepak N

2018年6月12日

Awesome Learning experience Thank You soo much.

創建者 Md Y A

2018年1月18日

I have learned a lot from this course. Thanks

創建者 RAMIRO C

2019年9月23日

I loved the course. Fantastic in every way

創建者 Laurenz R

2017年10月22日

Very good explanation of the given topics!

創建者 Solomon A

2017年10月5日

Great course. Very deep and practical.

創建者 Kuldeep S C

2020年11月30日

Very rigorous but rewarding course

創建者 Nan H

2020年6月2日

A very good course, I gained a lot!