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)....

Feb 13, 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.

Apr 15, 2016

I understood inferential statistics better with this course. Both teachers made the concepts clear for me. The R homework helps me review inferential statistics methods.

筛选依据：

创建者 王一丁

•Apr 24, 2016

It's too diffult for some of the questions in the Quiz. Have no idea or support to solve them.

创建者 Tay J

•Aug 07, 2017

While I appreciate the staff's efforts in making this MOOC and would love to thank them with five stars, I decided to give an average rating. I feel like too much material was packed in short lectures so that it is almost impossible to understand them fully (it gets increasingly so after week five). Oftentimes new concepts are explained and gone within seconds, and it largely comes down to memorizing formulas rather than understanding them. It seems like the lecturers were reading off a script that does not necessarily take into consideration the capacity of a student who just began learning inferential statistics.

I don't know - if one is already somewhat familiar with the materials or a genius then he or she may not have a problem following the course. But I, having had a reasonably good knowledge in basic statistics before the start of this course (obtained good results in both offline and online upper-secondary school-to- elementary freshman level basic statistics courses), frequently had to watch other MOOCs (e.g. there is a great course on inferential statistics on Khan Academy - longer videos for the same topics but they let you grasp the principles firmly) because I simply did not find the course videos sufficient.

On the positive side, I found the R-labs helpful. On top of that, quizzes and exams were quite difficult for a MOOC, which sometimes caused frustrations but still forced you to put a significant effort to learning.

On the negative side of the difficulty, sometimes I was stuck with utterly no way to proceed in the quizzes. Forums are not very active. Because the lectures are short and packed with content, they often did not contain any hands-on problem-solving procedures, and the student is left with abstract concepts and formulas at the quizzes. From time to time there are errors in the video graphics or quiz questions.

In the end, I did pass the course with about 94% final grade. However, I feel like I could have saved some time and frustration had the concepts been explained in more detail in a more learner-friendly manner and if there was a way to get some guidance (like hints) when stuck at certain quiz questions.

创建者 PHUONG T

•May 11, 2017

Fairly good

创建者 William

•Jul 30, 2019

The content is great,

the problem is, some of the questions and terms used in video and quizzes confused the students.

创建者 Gerard Y

•Jul 13, 2018

A pity: the learning objective is really interesting, but the course quality does not live up to expectations. Teachers rush too fast into videos, without taking time to elaborate on terms used in formulas, elaborate with one example, explaining pitfalls, or explaining how we should do things in practice (for example in relation with statistical software). Examples lack variety: I liked the videos on Chi-Square test which used a different analogy with paintings. Variations on cats statistics tend to blend together in memory, and be less efficient. There's also a lack of written textbook that we can consult as a reference. The tables and formulas pdf file is a start, but is lacking many formulas and tables, explanation of data used in formulas; some sections are not even in English. Last point (I keep the positive at the end), the codecamp was really good overall.

创建者 Elpida S

•Jul 17, 2018

First of all, it is a very demanding course. I claim that it could not be easy for everybody to complete it especially in the field of Social Sciences. Secondly, we must attend a lot of material. Both quiz and assigments are so challenging. That means that is a very stressful proccess, each of us should devote so much time in order to keep up with the deadlines. Moreover there are a lot of theoritical videos , a lot of types, of course is very difficult to put into practice.. All of the learners have busy life ( I suppose) and this course really does not help at all.

创建者 Jessica N

•Jun 29, 2017

Compared to previous courses in this series, I felt this course did not provide enough detailed examples of how to calculate the test statistics.

创建者 Tao G

•Apr 03, 2016

the content is too rich, and the explanation is too little. The no-feedback exam is misleading, difficult to pass. The course staff is not that helpful.

创建者 Zacharias V

•Feb 29, 2016

A couple of results in Q1 directly contradict the theory. Course is quite unreliable.

创建者 Jackson H

•Oct 08, 2017

Videos have massive typos in equations, quizzes are never clear as to how many decimal places they want (sometimes 3, sometimes 4, sometimes rounded), and quizzes require you complete problems but provide no examples in the videos.