Вернуться к Basic Statistics

звезд

Оценки: 3,712

•

Рецензии: 941

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: S A .

•16 авг. 2020 г.

great course

автор: Juan V

•6 окт. 2017 г.

Good course.

автор: ANAMIKA K

•9 мая 2020 г.

Very good

автор: Abdullahi A I

•25 февр. 2017 г.

thank you

автор: Harish

•13 мая 2016 г.

Too good

автор: Yeknath M

•8 апр. 2020 г.

nothing

автор: BHOOMIKA R H

•21 июля 2020 г.

GOOD

автор: sushant p

•20 июля 2020 г.

good

автор: Rowan W

•30 апр. 2019 г.

A

автор: Joanna F

•26 июня 2020 г.

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.

автор: Minhal S K

•27 сент. 2016 г.

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.

автор: Isheunoziva

•26 июня 2020 г.

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.

автор: Paul F

•11 февр. 2021 г.

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.

автор: Yulia K

•26 дек. 2020 г.

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.

автор: Jaciara T L

•17 сент. 2020 г.

I was very pleased with what I learned but I disappointed that examples used to explain statistical concepts were gender-biased. Either we were given examples with geese and shells or with men and beards: there were no women. Even with an example on R that started with the statement that Dutch people are the tallest in the world, the exercise used the average height for Dutch men, not Dutch women. Statistics is an area which is dominated by men and we should be encouraging women into statistical professions. I did not feel represented on the course.

автор: Marta B

•6 июля 2019 г.

The lectures (videos) are very clear and helpful but the R program is not useful. The most popular program to calculate statistics is SPSS or Excel. The R program is still not clear for me and I will not use it. I feel like I lost many hours trying to learn it. It would be much better if you use Excel because everyone has Office and is more or less familiar with this software. If I use R then I won't be sure if my calculations are correct. Anyway, the course explains basics of the statistics very well and now I can proceed with my research.

автор: Curt E

•14 мар. 2017 г.

The course has fun illustrations and a high quality of production, but the lessons themselves don't dive very deep. Ideas are introduced but not considered in depth. One such example is variance. We get the equations but not much insight into what it is a measure of and it's value. Additionally, and this might just be me, but the experiments used to illustrate examples at times are difficult to understand.

автор: John R

•19 апр. 2020 г.

The presentation of the course is exceptionally good and quite engaging.

The way that the material is presented is very dense and a lot of the content of the course is buried in a deluge of definitions. I think The course would benefit from a slower pace and a slower introduction to the main concepts.

I did not make it until the end but will try further offerings from this University

автор: David P S

•6 мая 2020 г.

Nowhere near as basic as I needed. It's all fine until you are expected to be a computer programmer, with a complete grasp of how to use R. I was so lost I did another stats course to try to get this one done, but the programming stuff was completely bewildering, so i gave up without success.

Perhaps a clearer description of the requirements of the course would help.

автор: Christelle C

•6 апр. 2017 г.

I am new to statistics and found most of the lessons difficult to understand, although I did pass the course and had taken the first two courses of the specialization before. More exercises would help. Also I do not plan on using R in the future so this part of the course was not very relevant to me, but it was not the hardest.

автор: Gabriel O M

•10 сент. 2018 г.

Some lectures were very good but others were extremely bad. Especially those given by the second professor were very confusing and not very well planned. One video even finished in the middle of a sentence. The exercises in R were also sometimes very badly designed. It was frustrating to try and finish them.

автор: Ryan J

•11 нояб. 2020 г.

Many of the explanations did not help for answering test questions. The R segment was nearly impossible because there was little explanation. The test questions did not always reflect how to use statistics but rather dealt with minutiae about details. Other than these aspects, the class was very useful.

автор: Monica A

•22 авг. 2020 г.

A great introduction to stats. However, the course could be improved. Learning to use R takes way more time than Coursera declared. A great disappointment but also a relief is that in the syllabus it says you can only take the final test once a month but you actually have 2 attempts every 24 hours.

автор: Kamal T

•3 мар. 2016 г.

The cartoons and animations used in this course really make statistics a lot easier and interesting. However few modules especially the later part of probability do not explain the concepts thoroughly. However, this is a great place to start!

Also, the addition of R exercises are a great idea

автор: Maxwell, L

•22 мая 2020 г.

It would be great if it was not assumes that we exactly knew how they came up with the numbers when setting up the equations. It would also be nice if the equations and material covered matched the material in the final exam. I did learn a lot but I would have liked to have learne

- Поиск цели и смысла жизни
- Понимание медицинских исследований
- Японский язык для начинающих
- Введение в облачные вычисления
- Основы самоосознанности
- Основы финансов
- Машинное обучение
- Машинное обучение с использованием Sas Viya
- Наука благополучия
- COVID-19: отслеживание контактов
- Искусственный интеллект для каждого
- Финансовые рынки
- Введение в психологию
- Начало работы с AWS
- Международный маркетинг
- C++
- Прогнозная аналитика и интеллектуальный анализ данных
- Получение навыков обучения от Калифорнийского университета в Сан-Диего
- Программирование для всех от Мичиганского университета
- Программирование на языке R от Университета Джонса Хопкинса
- Курс CPI для CBRS от Google

- Обработка естественного языка (NLP)
- Искусственный интеллект в медицине
- Мастер слова: письмо и редактирование
- Моделирование инфекционных заболеваний
- Американское произношение английского языка
- Автоматизация тестирования программного обеспечения
- Глубокое обучение
- Python для всех
- Наука о данных
- Основы бизнеса
- Навыки Excel для бизнеса
- Наука о данных с Python
- Финансы для каждого
- Навыки общения для инженеров
- Курс по продажам
- Управление карьерным ростом
- Бизнес-аналитика от Уортонской школы бизнеса
- Позитивная психология от Университета Пенсильвании
- Машинное обучение от Вашингтонского университета
- Графический дизайн от Калифорнийского института искусств

- Профессиональные сертификаты
- Сертификаты MasterTrack
- ИТ-поддержка Google
- Наука о данных IBM
- Инженерия данных от Google Cloud
- Прикладной искусственный интеллект от IBM
- Облачная архитектура от Google Cloud
- Аналитик по кибербезопасности от IBM
- ИТ-автоматизация с помощью Python от Google
- Специалист по работе с мейнфреймами на IBM z/OS
- Прикладное управление проектами от Калифорнийского университета в Ирвайне
- Сертификат по педагогическому дизайну
- Сертификат по проектированию и управлению в строительстве
- Сертификат по большим данным
- Сертификат по машинному обучению для аналитики
- Сертификат по управлению инновациями и предпринимательству
- Сертификат по экологии и устойчивому развитию
- Сертификат по социальной работе
- Сертификат по искусственному интеллекту и машинному обучению

- Степени в области компьютерных наук
- Степени в области бизнеса
- Степени в области общественного здравоохранения
- Степени в области науки о данных
- Степени бакалавра
- Бакалавриат в области компьютерных наук
- Магистр в области электротехнического проектирования
- Степень бакалавра
- Магистр в области управления
- Магистр компьютерных наук
- Магистр общественного здравоохранения
- Степень магистра в области бухгалтерского учета
- Магистр компьютерных и информационных технологий
- Диплом магистра делового администрирования онлайн
- Магистр прикладной науки о данных
- Международная программа MBA
- Магистр в области инноваций и предпринимательской деятельности
- Магистр компьютерных наук в области науки о данных
- Магистр в области компьютерных наук
- Магистр здравоохранения