Back to Basic Statistics

4.6

stars

3,546 ratings

•

903 reviews

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

Apr 20, 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

Sep 8, 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!!

Filter by:

By Mark B

•Oct 4, 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.

By 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!

By 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.

By Sofia W S

•Apr 12, 2020

Amazing course! I have learned more about statistics in this course than in my entire bachelor's and research practice. Some weeks (3,4 and 7) are a bit difficult and poorly explained: brace yourselves. Also, the R Labs are really helpful if your are interested in learning R programming as well. I've learned so much in this course (and in the other courses of this specialization) and this knowledge will be really useful when I start my research masters next fall.

If it's useful for someone: I completed this course in 3 weeks, because I'm in quarantine, so I'm not doing much work related tasks (covid-19 present here!)

By Tripp W

•Jun 16, 2020

The videos are phenomenal! Thanks for such a creative and thorough course.

My one recommendation for improvement - some of the formulas for different parameters were different between the course videos and the R environment in Datacamp. This led to some confusion.

By Francisco M A C

•Feb 20, 2019

This is an incredible curse. It has a lot of information, but they manage to deliver it in a dynamic, fun, and quite intuitive way, so it is really easy to develop an inner logic for all of the statistical concepts. Thank you very much.

By Pratiti S

•Aug 27, 2020

Brilliant material and the professors are amazing! I thoroughly enjoyed the course and would rate it 100% easy to understand , difficult concepts explained clearly, lots of exercises

By Mohammed R A

•Mar 3, 2019

Excellent for understanding the basic concepts and designed for those who have no clue what R is..

By Pau V A

•Aug 6, 2018

This is great! Every single concept is explained in avery easy and intuitive way! I loved it!

By Bill G

•Mar 1, 2019

Thanks for a great course. I really learned a lot. I came away with what I wanted: a basic grasp of key concepts in statistics that previously I had merely a superficial understanding of -- standard deviation, confidence interval, Pearson's r, etc. The video lectures were fantastic: clear, engaging, fun. I liked that I could pause them when I was confused on a point. A couple of criticisms, though. First, I found the r program frustrating at times. Sometimes it was used in a way that helped me to better understand the course's key ideas. But too often it was an exercise in guessing the obscure programing code to use. Since I'm unlikely to ever use the program again (and I suspect this is true of most students), overall I found the r programming of limited value. The other drawback of the course -- not your fault! -- was the same problem with all on-line courses. At times, I just wanted to ask a question or get a clarification on a point, but that just wan't an option. Finally, I think it would have been helpful had you provided an in-depth explanation of how to arrive at the correct answer for each question on the quizzes. For the quizzes, I was usually able to figure out the right answer (eventually), but not so for the final, which didn't provide any explanation as to why I got certain questions wrong. But, as I said, overall this was very good course. I got my money's worth.

By Stefano C

•Jun 15, 2019

This course was great to get an introduction of basic statistics and inferential statistics. The R exercises are great to test what you learned with practical exercises (in a real-life scenario where you have access to a tool like R). I cannot give 5 stars, because the chapters on probability are confusing and poorly explained: probabilities are one of the most difficult parts of statistics, so they require more pedagogy (with clear formulas to calculate conditional probabilities and step by step explanations)

By Edward C

•Dec 18, 2016

Overall, very good course. I thought the weakest sections were the ones taught by Prof. Emiel van Loon (the dark-haired one). I found him much less clear and engaging than Prof. Matthijs Roduijn (the blonde one). The R labs were fine for me because I have a background in programming, but people without that may need a lot of time to do them.

By Rhiannon D

•Nov 12, 2019

The probability section was super hard and not terribly well explained. I had to get help from my statistician friends in order to pass the probability density quiz and it was remarkably frustrating. Everything else was really good though. I like using R too, it's quite intuitive :)

By Jonason G

•May 14, 2016

Lovely accent, great lecture for the younger teacher. The older teacher really confuses me sometimes cos the language he used was very academic and hard to understand, besides he has a tendency to read other than lecture

By mridul b

•Jul 20, 2018

Some statistical things require explanation which was missing.

By Daniel S

•Sep 30, 2016

The lecturer does not clearly explain the topics very well especially on the topics in Probability and Distribution. His presentation in English is honestly quite hard to understand.

By Richard N B A

•Feb 9, 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.

By Charlotte M D

•Aug 19, 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.

By Scott P

•Aug 8, 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

By Clay C

•May 7, 2020

I just wanted to learn statistics, not also learn R, which has made completing this course impossible!

By YunLi

•Jan 11, 2016

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

By Dr. J P M

•May 2, 2020

Not a great course.

By Alejandro N J

•Jun 23, 2016

Excellent MOOC. A great introduction to the basic elements of statistics. I had studied statistics years ago in my bachelor but almost forgot everything. This course greatly helped me revive all the elementary concepts. The teachers explain complex things in simple terms easy to follow, and the funny examples have brought a smile to my face more than once and twice during the MOOC. Finally, the collaboration with professional illustrators adds great value to the course. A big deal of effort has gone into its making, and it truly pays off. I just wished there'd be an intermediate and advanced statistics course to keep digging into it!

Thanks a lot!

Alejandro

By Stacy H

•Jun 30, 2016

I hadn't touched math in any real way in years and this was a great re-introduction. The videos were fun and engaging, and while the material was challenging, I felt I got a lot out of it. I highly recommend it for people who need statistics for their work or for a degree program but who are feeling a little intimidated by it.

As far as feedback goes, I would have liked to get explanations for quiz questions I couldn't answer. I wish there was a way to say, "This is the quiz score I'd like to accept; now please explain to me the ones I missed." The lack of feedback on the quizzes was frustrating at times.

By gerald k

•Apr 19, 2016

This is a great course. It was challenging but not discouraging. I think that there is a high probability that I learned something very useful. Now that I have said the most important words now I would like to give a thumbs down on the Data Camp R section. I found it to be frustrating and discouraging. You can find better information and tutorials on YouTube. Check out"MarinStatsLectures. A text book is also a great help. I bought Elementary Statistics at a used book store for $4.00 US. And it correlated very nicely with the course. If you are interested in statistics this course is a good first step.

- Finding Purpose & Meaning in Life
- Understanding Medical Research
- Japanese for Beginners
- Introduction to Cloud Computing
- Foundations of Mindfulness
- Fundamentals of Finance
- Machine Learning
- Machine Learning Using Sas Viya
- The Science of Well Being
- Covid-19 Contact Tracing
- AI for Everyone
- Financial Markets
- Introduction to Psychology
- Getting Started with AWS
- International Marketing
- C++
- Predictive Analytics & Data Mining
- UCSD Learning How to Learn
- Michigan Programming for Everybody
- JHU R Programming
- Google CBRS CPI Training

- Natural Language Processing (NLP)
- AI for Medicine
- Good with Words: Writing & Editing
- Infections Disease Modeling
- The Pronounciation of American English
- Software Testing Automation
- Deep Learning
- Python for Everybody
- Data Science
- Business Foundations
- Excel Skills for Business
- Data Science with Python
- Finance for Everyone
- Communication Skills for Engineers
- Sales Training
- Career Brand Management
- Wharton Business Analytics
- Penn Positive Psychology
- Washington Machine Learning
- CalArts Graphic Design

- Professional Certificates
- MasterTrack Certificates
- Google IT Support
- IBM Data Science
- Google Cloud Data Engineering
- IBM Applied AI
- Google Cloud Architecture
- IBM Cybersecurity Analyst
- Google IT Automation with Python
- IBM z/OS Mainframe Practitioner
- UCI Applied Project Management
- Instructional Design Certificate
- Construction Engineering and Management Certificate
- Big Data Certificate
- Machine Learning for Analytics Certificate
- Innovation Management & Entrepreneurship Certificate
- Sustainabaility and Development Certificate
- Social Work Certificate
- AI and Machine Learning Certificate
- Spatial Data Analysis and Visualization Certificate

- Computer Science Degrees
- Business Degrees
- Public Health Degrees
- Data Science Degrees
- Bachelor's Degrees
- Bachelor of Computer Science
- MS Electrical Engineering
- Bachelor Completion Degree
- MS Management
- MS Computer Science
- MPH
- Accounting Master's Degree
- MCIT
- MBA Online
- Master of Applied Data Science
- Global MBA
- Master's of Innovation & Entrepreneurship
- MCS Data Science
- Master's in Computer Science
- Master's in Public Health