Volver a Inferential Statistics

4.4

321 calificaciones

•

89 revisiones

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.

Filtrar por:

por Priscilla R C

•Jul 10, 2019

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

por Francisco J G L

•Sep 11, 2019

Me ha hecho sufrir , estoy alegre de haber pasado OUIIIII

por Saurabh P

•Jan 07, 2019

Really a great course. It covers almost everything that is important in the subject. But maybe it could have been made better by adding the exercises more often than it is now as it covers a lot of syllabus.

por Dragos A

•Sep 14, 2018

The course is too compressed in my opinion but if you make it past the second week, the learning curve is not that steep anymore.

por Jiajing G

•Jul 06, 2018

The course is nice with much content and clear examples! So happy that I passed the final exam. But some transcripts in the videos are not correct and some steps in calculation were omitted. I hope reviews of quiz and exams are available.

por raunak r

•Jan 08, 2017

Not giving 5 stars only because it was fast paced. With a low grasping power i had to watch the video again and again. Otherwise the content in the video is to the point.

por Luis L C S

•Dec 12, 2016

Awesome however was a littler dificult to follow, I think it can be betther by a step by step practices...

por Richard J W

•Mar 29, 2016

A good introduction with very good videos and exercises. I'm only not giving 5 stars due to the relative lack of clarity in the final week and the lack of feedback on the final exam.

por Francisco P

•Jun 18, 2018

It is a great course it will be next course that I shall take when I have more time

por Eva

•Aug 31, 2017

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!

por Peng W

•Dec 20, 2016

Too fast.

por Di M B

•Jun 21, 2016

Very good course to learn bases of statistics. I enjoyned. Thak you to the teachers.

por Liza S

•Dec 16, 2016

I enjoyed this course. Being new to stats, I feel I needed more practice and extra examples. A lot of extra work and self-study helped me grasp and pass this course.

por 田野

•Jun 20, 2016

S

por Mariëlle S

•Jun 21, 2016

Great course, not easy because lots of information is shared in a short time. But totally worth it!

por Donald M

•Apr 15, 2018

Much more study required than the Basic Statistics course, I completed with 93% by using a notepad, pausing regularly and taking a lot of notes.

por Lai P Y

•Jan 04, 2018

Compare to Basic Statistics, this is indeed a challenging course but worth the effort.

por RAVIKA C

•Jun 10, 2019

It is a little tough. But has a good amount of syllabus!

por Yanbing S

•Jun 02, 2019

It's good for a person who needs a certificate urgently. But not good enough for someone who wants to master the subject.

The course is very rigorous in terms of the depth and width of the content. But for the later weeks, the videos were so succinct that many details are not explained well. For a beginner, this is apparently insufficient. I had to look it up on other websites to know what they are talking about (I also wished they had recommended a textbook). Also, the lack of practices also makes the course less valuable for someone who wants to actually be good at it.

por Lyra F

•Jul 14, 2019

The course helped me learn the main tenets of applied inferential statistics (I see it as applied because not much mathematical explanation on how the formulas came about here). Although my execution of statistical tests is not perfect by the time I completed it, I have largely understood what tests to use in what circumstances and to analyze problems in a statistical way. I appreciated Anne-Sylvie's clear delivery and the effective visuals in the videos. Without the visuals, it would have been hard to keep up with the pace of the course. The one star off is for the occasional confusion in delivery and questions in the final exam.

por Syberen v M

•Apr 07, 2019

I took this course as a follow up to "basic statistics". The course is dense and fast-paced, so that's something to prepare for. Here are my observations:

The good:

The R labs are a lot better compared to basic statistics, where they were a disaster. You'll put to use the built-in functions in R to calculate your results.

Also the general amount of information is nice, I feel like I learned a lot about inferential statistics.

The bad:

Sometimes the videos are too fast, functions are shown for 2 seconds not allowing time to absorb the material. I often have to go to other sources to clarify what was meant.

Also frustrating is that there's no feedback on the exams, you're left to guess what you did wrong. Multiple times I found out that it was a rounding error, but the amount of digits are not specified in the question, so you have to re-take the exam several times until you find the expected amount of digits.

Finally, some of the required formulas are not included in the "formulas and tables" document. I hope this will be fixed, since this is essential to passing the course successfully.

por Diego A

•Apr 11, 2016

Great job on the course material and labs, quizzes and the final exame however, tend to be very confusing.

por Simran S

•Apr 09, 2016

Lots of topics crammed into short videos. But still I was able to stick to it complete it. There are a few mistakes here and there that create confusion. Had to watch the videos over and over for some concepts (whcih is ok). All in all a good course but can be improved.

por 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.

por 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.