4.6
4,137 个评分
1,028 条评论

## 课程概述

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....

## 热门审阅

Jun 27, 2022

Instructors have provided concise explanations of the concepts. There are many examples considered that make statistics easier to understand! Also, the illustrations are fancy. I enjoyed every video!

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.

## 926 - 统计基础 的 950 个评论（共 1,017 个）

Jul 16, 2020

its nice experience......!

Apr 7, 2016

I enjoyed the class.

Jan 30, 2020

good, can be harder

Aug 3, 2020

Well composed !

Jun 25, 2016

Great course :)

Jun 28, 2021

Too much tests

Jun 21, 2020

Awesome course

Feb 3, 2018

great course~

Aug 16, 2020

great course

Oct 6, 2017

Good course.

Jun 12, 2021

great topic

Jul 16, 2021

very good.

May 9, 2020

Very good

Feb 25, 2017

thank you

May 13, 2016

Too good

Apr 8, 2020

nothing

Nov 21, 2021

good

Jul 21, 2020

GOOD

Jul 20, 2020

good

Apr 30, 2019

A

Jun 26, 2020

The videos were very clear and helpful. The material was straightforward and broken down well without being overly simplified or covering too-elementary concepts. The professors were easy to understand and pleasant to listen to. I think it does help to have an instructor to look at rather than just having writing and graphics on screen. The art was cute and the onscreen graphics were helpful. The examples were quirky and memorable, which is probably an under-appreciated element in mathematics.

However, there were no practice problems besides those in the videos, so there was basically one or two examples of each concept. It would be extremely helpful to have practice problems. I don't think that including practice problems and feedback would be that technologically difficult. Just a few multiple choice questions per lesson with comments explaining why a choice is correct or incorrect would be immensely helpful. The quizzes are somewhat like this, but the feedback is minimal. Alternatively, this course might include questions during the videos similar to in the Quantitative Methods course in this series. This would help to highlight important concepts and break down the videos somewhat more. I ended up having to look elsewhere for practice and other examples.

The R programming sections were not at all easy to follow. It was basically exercises without much of a lesson to teach how to do the exercises. I often ended up requesting the answer and working backward from that.

Sep 27, 2016

I have started this course again and again. Although the lectures themselves are clear enough, the quizzes are sometime so confusing and don't reflect the way that topic was taught. The worst part is R lab. I understand nothing of it. It makes no sense. I should not be part of a basic statistics course. I have wasted my money on a specialization that I can't get because I will not, and simply cannot learn R. They should have made that clear this would involve programming. I am only now thinking of learning from the videos but have given up the hope of getting a specialization certificate.

The instructor in the first two session was still engaging, but starting in the third lesson the instructor is so boring and his voice makes me drowsy. Plus his sentences are so long and confusing. He has a horrible way to explain something. They need to keep in mind this is BASIC statistics, so cut down on the jargon. He does introduce the terms in 3.01 but just after one video the words don't magically sit in my memory.

I've given 3 stars because although I have to work double hard just to make sense of what the instructor says by reading a book on basic statistics, at least the videos provide a structure, good examples and after watching them a few times things become clear.

Jun 26, 2020

As far as content is concerned, this course is a must for anyone serious with statistics. The content starts from descriptive statistics, moves on to probability then basics of inferential statistics which include estimation and hypothesis testing.

However, I gave it a 3-star for its inaccessibility. If you use a screen-reader with this course, you would find that most of the stuff would be inaccessible. The lecturer instead of saying out the formula on the board, just points to them and assumes you are seeing them. In that respect, you may need the help of someone to help you. To me, this defeats the whole purpose of learning: You need to be independent. So you end up guessing or making some readings outside the course if you want to pass.

A big plus though, goes to the R Labs by Datacamp: I think this course helps anyone new to statistical computing. I found the Labs really beneficial. Each exercise emphasises on the hands-on approach to everything in statistics: from preparing barplots, working out probabilities and confidence intervals. This hands-on approach takes out "theory" out of high school statistics and adds practice.

Feb 11, 2021

It gives a solid background on statistics, but has a few legitimate flaws that are very frustrating for the student:

-the R labs are a good idea, but in practice become somewhat of a waste of time, and I do not feel as though I have really learned any practical R

-starting week 3, there are several errors on the screen that still have not been updated (I'm taking this course in 2021)--this leads to a lot of frustration as you often struggle to figure out why the numbers on the screen are what they are, and then have to check the discussion forums for clarity. Also, at the end of week 3, the lessons start moving very quickly, and are compounded by these errors, which makes it extremely difficult to conceptualize what is being taught. I am now looking at wikipedia and other sites to learn the concepts at the end of chapter 3, as all it did was confuse me.

Dec 26, 2020

It was a good course, but not enough practice. There is practice in R lab, but I felt like it was mostly to get know functions in R language that could be used for statistics. R lab could not be replacement for the practice of problem-solving that was required for the last test. I wish also that the feedback was a little bit more explanatory. I am not sure how often mentor a reviewing the discussion board, because I hadn't see the answer to my questions, as well as to questions of other people. It is a pity, because it leaves people without understanding what was wrong with their answers and confused about topic. The course definitely required additional resource for complete understanding the topic, and it would nice to have a mentor that guides through difficult questions.