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.

Mar 06, 2016

This course is really awesome. Designed well. Looks like a lot of efforts have been taken by the team to build this course. Kudos to everyone. Keep up the good work and thank you very much.

필터링 기준:

교육 기관: Clement

•Feb 25, 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.

교육 기관: yazhini c

•Aug 16, 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!

교육 기관: Ivan C

•Jan 07, 2016

Damn R-Lab

교육 기관: Richard N B A

•Feb 09, 2016

Puerile, made up examples with made up data, no deeper treatment of the mathematics involved than the here-is-a-magic-formula-use-it approach and mistakes (including serious conceptual and factual errors) evident in the quizzes and the R labs. Far better to look out for the "Data Analysis and Statistical Inference" course by Duke on Coursera that is presented by a passionate statistics teacher, covers the same material (and more) and provides a far better introduction to R than this course.

One of the stated purposes of this specialization is to clean up the way social scientists conduct science and are perceived as scientists; in this respect, it appears that the worst enemies of social scientists are social scientists.

교육 기관: Charlotte M D

•Aug 20, 2017

I am a complete novice to inferential statistics, probability and R programming. The video lectures were clear enough, but they did not cover everything in the quizzes- quite a few mathematical leaps had to be made, so proceed with caution if mathematical dexterity is not your strong suit. The probability lectures were especially riddled with gaps and leaps in logic that I struggled to follow.

What is more, the R programming does not stick to the vocabulary and concepts presented in the video material. The R assignments are disjointed, unclear, and do not advance, nor compliment, the material.

교육 기관: 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.

교육 기관: 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!

교육 기관: 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.

교육 기관: 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.

교육 기관: Scott P

•Aug 08, 2016

this course was a waste of my time; luckily I found out after wasting only 6 hours on the preview. this course apparently requires a level of probability knowledge I don't

교육 기관: 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.

교육 기관: YunLi

•Jan 11, 2016

Good lectures, but the R-lab is horrible. Do not take this class.