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学生对 阿姆斯特丹大学 提供的 统计基础 的评价和反馈

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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....



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!


Apr 20, 2016

This is a nice course...thanks for providing such a great content from University of Amserdam.

Please allow us to complete the course as I have to wait till the session starts for week 2 lessions.


776 - 统计基础 的 800 个评论(共 1,049 个)

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创建者 Deepak R

Apr 1, 2019


创建者 Tomislav S

May 11, 2020

Even though I graded 5 stars, I would actually prefer to grade 4,5 stars this course. I liked many things, but some were really frustrating. Pros: the overall knowledge that is offered in this course (BA level), course structure, quizzes. Many students critized the course integration with R, but I do like this fact. I am aware they could have organized the practical part with some other tools, but for me R is a necessity and a must. However, there are some drawbacks. 1. The presentation quality between two instructors was noticeable. Somehow, one of them was repeating more, had a slower pace, more vivid examples, which I prefer. 2. There are several important mistakes with numbers in the presentation slides. Many students have already noticed that, so it's a pitty no one corrected them. 3. This drawback is more for DataCamp, and not for this course, but the spelling was really bad. Too many obvious mistakes. 4. Final test. It was quite demanding for me. I still don't know how one could answer 30 math questions, many of which include calculating, for only 1 hour of time!? Also, some questions were really tough and I haven't found an answer anywhere in my lectures. There are at least 3 answers that I don't know how to explain why were (in)correct.

I plan to take another statistics course in Coursera, as well as at Khan Academy, so I will be able to compare and evaluate more adequately the knowledge presented. For the time being, I would recommend this course!

创建者 Linda J

Aug 24, 2017

Very clear course. It really started with the basics, so I could understand everything. The set-up (transcripts with videos, helpful animations in the videos, R labs, quizzes) was really designed to get the most out of it. I learned a lot from it.

Two points of approvement:

1) Feedback on the quizzes! I thought it was really a loss that I couldn't see what I did wrong in the quiz (you can see which questions were wrong, but not which answer you chose and which was the right one) and that there was no explanation of why the answer was wrong. This way, I learned nothing from my mistakes in the quizzes, unfortunetely.

2) Quizzes took me way more time than what was designated for them, because some of the questions had to be answered in R or manually, and the course didn't teach me a quick way to calculate the answer (or sometimes it did, but the small data sets given in the quizzes aren't implemented in R so doing this manually also took quite some time). This way, a simple multiple-choice question could consume way to much work because you sometimes had to do a lot of tedious manual work.