Retour à Basic Statistics

4.6

étoiles

3,460 évaluations

•

878 avis

Understanding statistics is essential to understand research in the social and behavioral sciences. In this course you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them. This course will also prepare you for the next course in the specialization - the course Inferential Statistics.
In the first part of the course we will discuss methods of descriptive statistics. You will learn what cases and variables are and how you can compute measures of central tendency (mean, median and mode) and dispersion (standard deviation and variance). Next, we discuss how to assess relationships between variables, and we introduce the concepts correlation and regression.
The second part of the course is concerned with the basics of probability: calculating probabilities, probability distributions and sampling distributions. You need to know about these things in order to understand how inferential statistics work.
The third part of the course consists of an introduction to methods of inferential statistics - methods that help us decide whether the patterns we see in our data are strong enough to draw conclusions about the underlying population we are interested in. We will discuss confidence intervals and significance tests.
You will not only learn about all these statistical concepts, you will also be trained to calculate and generate these statistics yourself using freely available statistical software....

PG

20 avr. 2016

This is a nice course...thanks for providing such a great content from University of Amserdam.\n\nPlease allow us to complete the course as I have to wait till the session starts for week 2 lessions.

JB

8 sept. 2020

Thank You, @University_of_Amsterdam for this wonderful course. I have really benefited a lot from this course. Thank you, Dr. Matthijs Rooduijn for making this course so lively and interesting!!

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par Peter W

•3 juil. 2020

The quality of the teaching was uneven. Good effort to make difficult topics understandable in places, but poor in others. I needed to supplement with other materials in order to grasp some of the concepts.

par Bidhan D

•21 juin 2020

Although it is hard to understand week three and four. But if anyone to understand the basic knowledge regarding statistics, i think this course will be helpful to any new learner from any background.

par Nikita F

•13 sept. 2017

Unfortunately I didn't like this course – the basic things are explained in great details (which is not always necessary), but more complicated terms are not covered in the way they should.

par SRINIVAS R

•2 avr. 2016

some of the videos were outstanding and easy to understand. Need more handholding for understanding of concepts and review/explanation of the quiz results will reinforce learning further.

par Eunice H

•4 janv. 2020

I was expecting to learn basic statistic before diving into the programming. I did not take this class to get familiar with R programming. And it slow me down.

par Christina P

•26 oct. 2017

It was a really nice and informative course. As a statistics rookie, I can say with confidence that I now know the basics of Statistics! Thank you very much!

par Ladden D N G U

•11 oct. 2020

VERY INFORMATIVE COURSE, YET I AM NOT THAT FAN OF THE rLAB BECAUSE OF THEIR INSTRUCTIONS THAT ARE HARD TO GET.

par Bhupesh P

•3 mars 2017

Course material is not enough, you need to also refer at least one reference book as well.

par Yutian L

•16 mai 2017

if we can have a review before the final exam will help a lot. and the r lab is so hard.

par Pankaj M

•25 nov. 2016

2 Stars less because they should have included R video tutorials

par SUNEWAD R L

•1 août 2020

good for the users , who wants to learn R lab coading.

par Sujoy S

•2 juin 2019

Very tuff quiz questions

par Rasmus B

•29 juin 2019

quite hard

par asha s m

•2 juil. 2020

THANKS

par Navya V

•2 août 2020

good

par Mutcherla S

•30 mai 2020

good

par Anastasiya K

•28 avr. 2020

The course is good because it collects pieces of information together if you have studied something before. But I went through it for a very long time (relative to other specialization courses) and lost motivation several times, had to take breaks. Some topics are not described in such detail and with incomprehensible examples, which is why it is go difficult to solve problems. Tasks with R are generally difficult - but not because it's code (i'm good with it) – most often tasks were not related to lectures in the subject, and often instead of using functions and other convenient methods in R, you had to solve everything manually, simply substituting the numbers in the formula. But what's the point then in the code?

I would also like to draw attention to the fact that it’s very difficult to pass tests, sometimes the question and answer options are ambiguous, or it seems that there can be more than one answer.

Also important is the fact that the curators do not answer questions at all on the forum, I met questions written six months or a few months ago - and they were unanswered. How so?

In general, I am glad that I took this course, but I can’t say that it practically helped me. You will have to watch other courses to fill in the gaps and understand what was not explained here.

par Courtney v S

•10 nov. 2016

Not very helpful. In the homework I spent more time wrestling with commands in R than actually gaining an understanding of the subject matter.

Also, I really didn't need so many subject matter examples about the professor's baby's pooping habits. (And my family is Dutch with all the offensive humor that comes with it, so it's not just a matter of the sense of humor not translating)

I'm re-taking Statistics with Calculus online at my local state university and frankly, I can't notice any benefit from taking this course first. My current online Statistics with Calculus course is rewarding and I feel like I'm truly gaining mastery of the topics, whereas in the Basic Statistics course I was floundering.

The graphics in the way the lessons are presented are well done! But I would have been just fine with fewer graphics if it meant more worked-through examples.

par Bank E

•23 juil. 2020

The instructor failed to explain many parts; such as why we don't use T-distribution for proportion, why use n-1 instead of n in some equations, etc. The discussion forum is sooo quiet, I appreciate some students who try to help other out. R lab is the most annoying part, you barely need any understanding at all; all you need is remembering the function and understand the convention what instructions are telling you (which is so varying or sometimes not telling you and you have to go back to see what it is in the previous questions). I feel R lab is not useful.

par Dafna M

•6 déc. 2019

Most of the courses didn't feel like basic statistics, they were very hard, plus a lot of the presentations were difficult to understand. I felt that there is a significant disparity between the two lecturers; the way they present the learnt materials is very different. In several times i had a gap and had to look for more information online. This is called "basic statistics" and it felt like i was supposed to start the course with a previous knowledge which i didn't have.

par Monica H

•12 oct. 2020

I struggled with understanding the concepts. At the first read, they made sense, but when trying to solve problems they stopped making sense. There were errors in the calculations too, and more examples would have really helped.

par Ante

•15 déc. 2019

This course is more about learning R-programming which is totally useless for me. The videos are nice. Try instead buying the book and do the excercises with python or excel.

par Andrea F

•29 déc. 2016

I've only gotten started, but there seems some assumptions made about how much we know and how quickly we can pick up these new terms and ideas.

par Clem O

•25 févr. 2019

The program is good. The videos not so much. The professors are speaking pretty fast. It would have been good to have some written material.

par yazhini c

•16 août 2016

R labs are too tedious for people with medical or science background! we need explanations rather than trying to figure it out on our own!

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