Retour à Basic Statistics

4.6

étoiles

3,165 évaluations

•

820 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....

Apr 21, 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.

Aug 06, 2016

One of the best courses of statistics for the beginners. The concepts are well explained, the learning path well researched and above everything the R labs were ideal for the beginners.

Filtrer par :

par Mark v d S

•Apr 06, 2019

This course is very good. Make sure you know very basic principals of R-programming, or just programming in general. It doesn't have to be much, but a little knowledge will spare a lot of frustration.

There are a few errors in the course and the quiz answers here and there, and the forum is not maintained well. Brace for week 3 and 4! The instructor speaks very fast and unclear for some people (especially non native speakers I guess), and the material gets quite tricky in these weeks. However, it all gets a bit easier again later.

So much for my whining. The instructor(s) actually uses a lot of fun ways to dive into statistic methods. week 6 and 7 were an absolute blast to me. Finally, the course really teaches you a lot about basic statistics! So it does exactly what it is meant to do.

p.s. Don't stress for your final exam. You get more attempts per month than it says. Take a few hours for it though.

par Deleted A

•Aug 06, 2016

One of the best courses of statistics for the beginners. The concepts are well explained, the learning path well researched and above everything the R labs were ideal for the beginners.

par Mike P

•Jan 08, 2019

This class is fast paced. Weeks 1 and 2 are the equivalent of Stats 101 at a university. Some of the videos cover the topics too fast and would benefit from some additional examples. To truly learn the topics, I visit other sites that cover the topics in more detail, presented in a different manner, and provide more examples.

Pros

Comprehensive

Great illustrations

Cons

Requirement time is grossly underestimated in the course overview

Quiz questions can be stated in a confusing manner

Videos can cover topics too fast without enough examples or information

par Adya K

•Apr 02, 2019

The course is good so far...However be warned that you need to know the basics of a computing language called R. If you don't know this it would set you back by a many days. Then the option is given to reset deadlines and they charge regardless.

There is no advice stating "Know R " before signing up.

par Syberen v M

•Feb 09, 2019

The instructional videos are clear, nicely illustrated, and contain good examples that make you get an intuitive grasp of the course material. Exams are good and the feedback provided references the lecture in question, so that you can re-watch it, very nice.

The biggest drawback of this course are the R labs. The questions are extremely sloppy, full of spelling errors. Most of the questions could have been asked during the regular exam, since all you are doing is submitting answers, no programming needed at all. If there are multiple questions in one section, there is no way of knowing which one you got wrong, it will simply say "something isn't right", which is very infuriating.

I hope they will shift these questions from the R lab to the regular exam. Given that I'm paying a considerable monthly fee to take this course, I would have definitely expected this aspect to be better, and feedback to be taken seriously, which I don't think it is unfortunately.

par Yuqin L

•Nov 20, 2017

Week 3 really puts me off

par Alessandro F

•Jan 26, 2017

great introduction to statistics with no prior knowledge required. Although in parts has been challenging, for me is the right degree of difficulty to push an individual to learning.

par Summer

•Mar 29, 2019

The instructor spend most of the time explaining the easy part like calculate the numbers but ignore the difficult part like explaining the concept and derive the equations. Although the whole team spend a lot of time preparing the course and try to make the course vivid, as a student with minimal statistic knowledge it is still really important for me to understand each concept and equations instead of just reciting them. For every equations that appeared in this course I was asking why, but there is no explanation of why this equation is like this and how you derive, there are just follow up examples to put the number in the equation and calculate them.

Thanks for the efforts your team put in this course.

par Big W

•Jan 08, 2016

---------- way too much time is devoted to introducing definitions and way too little time is given for student practicing and review . the presenter's accent is constantly impeding instant recognition of what he's saying. the subtitles sometimes don't accurately represent what he's saying. sometimes there are misspellings - which makes it even harder to know what he's saying. this student was inundated with formulas that needed to be practiced - and i didn't even have time to write them down !

par Emilly M

•Jan 09, 2016

Only the firs week of this course, but I can already tell that it's going to be incredibly useful to me. I've learned a lot and especially love the introduction to R through datacamp!

par Xavier S

•Dec 04, 2018

I finished this course in around 3 weeks (instead of 8 because I needed to learn fast), it was dense but also a wonderful experience. Nice teachers, nice quizz, nice R-labs. Plenty of examples, easy to follow. I cannot give 5 stars because, unfortunately, there are some mistakes in few lectures and the questions in the quizz and R-lab are sometimes not thoroughly enough written, (clearly not written as do pure mathematicians), and consequently the answers will sometimes depends on your interpretation. In this case, (a little bit frustrating !), you just have to be patient and to try to understand how the teachers think.

However, I STRONGLY recommend this course that is increadibly pedagogical.

par Stepheni F

•Jan 01, 2020

I would give this course a 0 if it were an option. I have no use of R, I do not need nor will I ever use R. I am not interested in wasting weeks of my time learning a programming platform that I do not need. It is ridiculous that 80% of the grade depends upon me knowing how to use a programming platform! NO thank you!

par Kanglu Y

•Feb 07, 2016

I love the main lecture of the statistics. The Subject is fun. After couple lecture, my mind was very clear.

But most of the time I'm working on the statistics software name R. I think it would be better if require R knowledge. If not, student like me will need more than weeks to get use to R. I don't mean learn another software is bad idea. I will always like to learn something new. That's why I go MOOC. What I mean is R and Basic Statistics should be separated. First R, than Basic Statistic. Or first Basic Statistic than R.

I really enjoy the class. but the extra is a bit heavy for me.

par chengxiaoxue

•Oct 13, 2017

I do not understand why the instructors cannot use simple, daily-life examples. Why should the invented islands, rocket be involved in their examples? For a person who has no idea about planes, we should try hard to understand something unnecessary ! Please do not just stay in the ivory tower! Think about real life.

par Daithi M W

•Apr 19, 2016

The course is as much about computer programming as it is about statistics. The statistics I can do with pen and paper; the programming, I found very, very unhelpful and confusing. Eventually, I gave up on the course.

par Keith C

•Jul 05, 2018

I got to know about this course as it was a prerequisite for a MS in Business Analytics program I will be joining this Fall. I do have some background in this subject due to a previous masters degree, as well as work experience, but this course was an extremely helpful refresher of the basic concepts that one needs to know. What I liked most about this course was the crisp explanations provided in the instructional videos; without taking too much time in delivering the required message. I also liked the fact that the quizzes focused more on testing the understanding of the concept rather than expecting me to perform complicated multi-page calculations. Would recommend this as a very useful starting point for others like me. It would be helpful if some kind of a diagnostic exam was added at the start of the course so that students of different backgrounds could assess if they're ready for the course or not.

par Michelle D

•Oct 24, 2017

Overall, I find this course really helpful for those who don't have much background in statistics. The lecturers and illustrators have done a very good job explaining hard concepts through fun examples. Some flaws I'd like to mention: The the discussion forum is not very hectic, and in some weeks, looks like an abandoned island. The course has not provided learners with sufficient materials, such as standard z-table, t-table, etc. Several concepts are not thoroughly explained (the P-value, for example), perhaps due to their toughness, so good articles with elaborate explanation on these concepts would be a great addition. And finally, while assignment questions are good and comprehensive in general, some of them need modification to avoid ambiguity (by adding information about whether they are considering one-tailed or two-tailed test or providing z-score used in the question, etc) for learners.

par Du F

•Apr 22, 2019

非常完美~~~ 我爱了！！！敲稀饭这个组合 可萌可攻可 ... 这个basic statistics的课程 很稀饭很稀饭很稀饭

par Luis O C

•May 12, 2019

It is a great course, I learned a lot but some recommendations.

The teachers should revisit some R classes, I found some typos and specially week 7 R Class, since most of the class are problems based on the videoclasses but more advanced, getting together topics already taught in a more difficult way, a class about all that is recommended, I understood almost nothing and it was more like guessing.

Some exams need extra explanation of the reasons why an answer is wrong or why the right answer is the correct one.

par Susan M

•Jun 23, 2016

Uses R with no explanation. Why does it use a challenging programming language that is not the point. The point is to learn statistics.

Use Statcrunch - so students can focus on statistics not programming

par h

•Jan 14, 2017

Way too much videos and too little hands-on learning. Felt like the course mostly taught you to remember stuff, and not actually learning a skill, though I broke the course early.

par Mark B

•Oct 04, 2018

I'd like to brush up on stat without being forced to learn R. I've already invested quite of bit of my time and resources into learning Python.

par Farhan M R

•Apr 23, 2020

Finally, I notice this course extremely useful for people who haven't got abundant background in statistics. The lecturers and illustrators have done a awfully sensible job explaining arduous ideas through fun examples. Some flaws i would wish to mention: The the discussion forum isn't terribly feverish, and in some weeks, sounds like associate degree abandoned island. The course has not provided learners with comfortable materials, like commonplace z-table, t-table, etc. many ideas aren't completely explained (the P-value, for example), maybe because of their toughness, therefore sensible articles with elaborate rationalization on these ideas would be an excellent addition. and eventually, whereas assignment queries ar sensible and comprehensive generally, a number of them want modification to avoid ambiguity (by adding info regarding whether or not they ar considering one-tailed or two-tailed check or providing z-score employed in the question, etc) for learners.

par Ravi R

•Mar 15, 2020

Definitely a solid introduction to statistics- I found that the course was broken down into nice, digestible chunks where every lecture consisted of explaining a single topic over 4-10 minutes that would be built on over the course of every module. The quality of the videos is good, and the lecturers do a good job of explaining the concepts in a clear and concise manner.

I invested easily twice (if not more) the stated weekly study time in order to internalize the concepts being presented in the course, and I would highly recommend others do the same if they want to get the most out of the course.

The only thing I missed were perhaps further practice exercises with solutions, beyond those covered in the lecture or practicals. That would be the only neutral point in an otherwise very good course!

par Lola C

•Apr 22, 2020

I really loved this course. I sat down for a week or so and dedicated myself to completing it, and I learnt a ridiculous amount from it. The videos are clear, and cover a wide range of areas within statistics. As long as you focus, and dedicate time to properly pay attention, write notes, give their examples a go before continuing the video, and to learn where you went wrong, you will find this course very useful! Though some videos seem like they could be more concise, their explanations and examples have allowed me to vividly picture the different concepts, and remember them! (ALSO) To be able to learn the basics of a programming language in such a short amount of time is great, and the labs really allow you to revise over the week's topics.

- L'IA pour tous
- Introduction à TensorFlow
- Réseau de neurones et deep learning
- Algorithmes, Partie 1
- Algorithmes, Partie 2
- Apprentissage automatique
- Apprentissage automatique avec Python
- Apprentissage automatique à l'aide de SAS Viya
- La programmation en R
- Intro à la programmation avec Matlab
- Analyse des données avec Python
- Principes de base d'AWS : Going Cloud Native
- Bases de Google Cloud Platform
- Ingénierie de la fiabilité du site
- Parler un anglais professionnel
- La science du bien-être
- Apprendre à apprendre
- Marchés financiers
- Tests d'hypothèses dans la santé publique
- Bases du leadership au quotidien

- Deep Learning
- Le Python pour tous
- Science des données
- Science des données appliquée avec Python
- Bases de la gestion d'entreprise
- Architecture avec Google Cloud Platform
- Ingénierie des données sur Google Cloud Platform
- Excel à MySQL
- Apprentissage automatique avancé
- Mathématiques pour l'apprentissage automatique
- Voiture autonome
- Révolutions Blockchains pour l'entreprise
- Business Analytics
- Compétences Excel pour l'entreprise
- Marketing numérique
- Analyse statistique avec R pour la santé publique
- Bases de l'immunologie
- Anatomie
- Gestion de l'innovation et du design thinking
- Bases de la psychologie positive