Вернуться к Basic Statistics

звезд

Оценки: 3,826

•

Рецензии: 972

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

20 апр. 2016 г.

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.

DA

28 янв. 2021 г.

great course with good videos and examples. Very good course for learning the basic statistics. Unfortunately the week 3 is the most misunderstanding module, nevertheless very good and understanding

Фильтр по:

автор: DOMINIC P

•14 июля 2020 г.

poli

автор: Utsav M

•14 июля 2020 г.

Good

автор: �SADHARAN G

•14 июля 2020 г.

Good

автор: Cui L

•22 июня 2020 г.

good

автор: Priyanka A

•4 июня 2020 г.

GOOD

автор: avaneesh k

•25 апр. 2019 г.

good

автор: Wendong Y

•19 февр. 2018 г.

good

автор: Trung-Duy ( N

•23 сент. 2017 г.

Good

автор: praveen k

•3 апр. 2016 г.

Good

автор: Niharika N L

•3 авг. 2020 г.

NO

автор: BONG H K

•22 июня 2020 г.

ㅇㅇ

автор: Padmini M

•30 июля 2020 г.

.

автор: MAMATHA G

•23 июня 2020 г.

.

автор: Deepak R

•1 апр. 2019 г.

V

автор: Tomislav S

•11 мая 2020 г.

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!

автор: Linda J

•24 авг. 2017 г.

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.

автор: Vicky G

•6 февр. 2020 г.

I love the vivid examples, and the all the visual explanations. They really helped with understanding the concepts. The assignments and the R exercises are well designed and align perfectly with the course content which helps as well.

Meanwhile I wish there was more explanation about the math behind the formulas (as to how those formulas were derived) instead of just teaching us how to put numbers into those formulas. That way we'd be able to better understand the "why" behind the fascinating data behaviors. For instance why do we say when n >= 30 then the sampling distribution of sample mean is normally distributed? Why when number of success >= 15 and number of failures >=15 then the sampling distribution of sample proportion is normally distributed? What are the actual reasons behind using t-table instead of z-table when we do not know the population σ? Just a couple examples off the top of my head.

автор: Eva D

•11 авг. 2018 г.

This is a good course, and I would recommend it to anyone who needs an introduction to statistics. My main criticism is that now that the course is up and running, nobody seems to care much about maintenance. Some of the lectures and R-labs have mistakes in them. I understand that you cannot redo the videos, but it would be extremely helpful if you would create a printable document containing all identified errors, that students can check while watching the videos or doing the labs. Expecting students to go through years of postings on the forum to figure out if they misunderstood something or whether there was an error in the materials is unrealistic. It would also decrease the workload of tutors that receive the same questions over and over again. On that note, while some questions in the forum get answered very quickly, others remain unanswered for months.

автор: Lieke S

•28 февр. 2016 г.

In my opinion this course is a good way to learn basic statistics. I do think the R part and the statistics part could be more integrated in order to learn R better and to use it more efficiently. For me the studytime was double the time that was stated even though I was already familiar with some of the concepts and calculations. I feel like some weeks the subjects should have gotten a little more explanation with video's or other supportive material, maybe some assigments to make in order to check wether you know and understand the material. Maybe you could compare content and way of teaching to the Duke University statistics course, this is not a better course per se but does do some things differently whilst both teaching stats and R.

автор: Greig

•20 июня 2021 г.

I think the course content is very good. The videos are done really well. The videos are so good that they made me lazy with making notes. I could fairly easily recall the video content for the weekly quiz, so I didn't make notes. But with the exam I couldn't remember everything that we've done several weeks ago. So I had to look-up the rules and formulas in the transcripts. But, I think the transcripts should show the formulas. If the formulas were in the transcripts, it would be much quicker to find the relevant information and apply it to the problem. Or maybe provide a course summary / text book, which makes it easy to determine what the name of a variable is, when to use t-score or z-score, etc.

автор: Chris L

•5 февр. 2018 г.

Much better than the Univ. of Ohio introduction to Python e-course. The lecturers are more interesting and better produced. Likewise, the r course is better structured with more questions that build upon one another.

Down side: a lot of spelling mistakes, particularly in the r package portion. Also, some of the r questions were not intuitive, even after seeing the clues and/or answers. Finally, I still don't feel very competent at applying various formulas or the reasoning behind some of the statistical measures. I think the course would be better with some practical coding examples and examples after each lecturer video instead of all grouped up at the end of each week.

автор: Lauren A

•10 сент. 2017 г.

I genuinely enjoyed this class and learned a lot, but it was difficult and very time-consuming. I spent hours and hours on it. I just spent a total of around 7 hours on the final exam and still managed to fail it the first time. If your strengths don't lie in numbers (and apparently, mine don't), expect to spend more time on this course than on others. The lows are lower in this course than in other courses in this series (frustration), but the highs are definitely higher in this course than in the others (greater feelings of accomplishment when you finally figure something out). I also loved/hated learning R and I think you will, too. In the end, I think it's worth it.

автор: Jerry Z

•25 апр. 2020 г.

The videos from the first professor were amazing and the examples he gave were very important to better my understanding of when/how to use the equations. The use of R was nice but not necessary at all and it hindered my understanding of the course. I wish there would have been more work in the videos with how to use R and then work with it after. In R, the "hints" were not always good hints or had anything to do with the scenario and it became increasingly frustrating to use R with no experience and it did not seem to help with my understanding of statistics at all.

автор: Anna T

•15 мая 2020 г.

Overall it is a good course with the professors explaining many concepts through real world simple examples. But, sometimes I felt some videos needed more explanations. Again, I wish the answers to exams in feedback had more precise explanations. Whenever I felt something was not fully understood, I tried learning with other online resources.(like Khan academy AP Statistics course has lots of maths problems which make the concepts more clear). Again, one of the biggest drawback of this course is that it lacks handouts. Hence, always make notes while studying.

автор: Jens B

•26 мар. 2016 г.

This course has given me a much better understanding of many concepts I never understood while studying at university - Like the sampling distribution etc. and I can recommend it...

The only "but" is... I can see from the discussions that some (many?) students have problems with the "R" assignments. I have been programming previously, so I have not have had these problems. I would though like that these "R" assignments where easier to print or collect in a PDF document, so that I could easily use it as a "howto" later.

- Google Data Analyst
- Управление проектами от Google
- UX-дизайн от Google
- ИТ-поддержка Google
- Наука о данных IBM
- Аналитик данных от IBM
- Анализ данных с помощью Excel и R от IBM
- Аналитик по кибербезопасности от IBM
- Маркетинг в социальных сетях от Facebook
- Разработчик комплексных облачных приложений IBM
- Представитель по развитию продаж от Salesforce
- Сбытовые операции Salesforce
- Soporte de Tecnologías de la Información de Google
- Certificado profesional de Suporte em TI do Google
- ИТ-автоматизация с помощью Python от Google
- DeepLearning.AI Tensorflow
- Popular Cybersecurity Certifications
- Popular SQL Certifications
- Popular IT Certifications
- See all certificates

- бесплатные курсы
- Изучите иностранный язык
- Python
- Java
- веб-дизайн
- SQL
- Cursos Gratis
- Microsoft Excel
- Управление проектами
- Безопасность в киберпространстве
- Людские ресурсы
- Data Science Free Courses
- говорить на английском
- Content Writing
- Веб-разработка: полный спектр технологий
- Искусственный интеллект
- Программирование на языке C
- Навыки общения
- Блокчейн
- Просмотреть все курсы

- Навыки для команд по науке о данных
- Принятие решений на основе данных
- Навыки в области программной инженерии
- Навыки межличностного общения для проектных групп
- Управленческие навыки
- Навыки в области маркетинга
- Навыки для отделов продаж
- Навыки менеджера по продукту
- Навыки в области финансов
- Android Development Projects
- TensorFlow and Keras Projects
- Python для всех
- Глубокое обучение
- Навыки Excel для бизнеса
- Основы бизнеса
- Машинное обучение
- AWS Fundamentals
- Data Engineering Foundations
- Data Analyst Skills
- Skills for UX Designers

- MasterTrack® Certificates
- Профессиональные сертификаты
- University Certificates
- MBA & Business Degrees
- Степени в области науки о данных
- Степени в области компьютерных наук
- Дипломные программы по анализу данных
- Степени в области общественного здравоохранения
- Social Sciences Degrees
- Дипломные программы в области управления
- Degrees from Top European Universities
- Дипломы магистра
- Степени бакалавра
- Degrees with a Performance Pathway
- Бакалаврские курсы
- What is a Bachelor's Degree?
- How Long Does a Master's Degree Take?
- Is an Online MBA Worth It?
- 7 Ways to Pay for Graduate School
- Просмотреть все степени