Zurück zu Inferential Statistics

4.8

Sterne

1,893 Bewertungen

•

358 Bewertungen

This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data...

MN

Mar 01, 2017

Great course. If you put in a little effort, you will come out with a lot of new knowledge. I recommend using the book after you have seen the movies. It gives a deeper picture of how it works. Great!

ZC

Aug 24, 2017

This course by Professor Çetinkaya-Rundel is awesome because it is taught in a very clear and vivid way. Lab section and forum are so dope that I love them so much! Definitely strong recommendation!!!

Filtern nach:

von Rui Z

•May 14, 2019

Professor Mine is terrific. I'm sure she has a great depth of knowledge and grateful that she's able to deliver her knowledge out to listeners. She uses meaningful examples all along the course, no dry pure mathematical cases at all. That helps a ton to digest concepts. And she constantly repeat some core concepts and how to interpret a statistic right. I didn't realize how important this was until I was challenged with questions, then I came back and hear again her interpretation, and the whole thing became clearer. She's one of the best professors I've ever listened to, and I've been through grad school, met so many professors.

The current mentor Rolf was great at supporting. He answers a lot of questions in the forum. He's very responsible and supportive. So if you're considering on taking this course, take it now as mentor will change!

I haven't finished the course yet, but the enrollment rate seems to be quite decent, so I wouldn't expect it to take too long to get final project reviewed and get certificate. I assume this is an important issue for any course takers.

The only downside is that there could be more R code teaching, especially on complicated simulations. That way it may be more friendly to R beginners. I know it's important to do research ourselves for codes, but beginners could lack of proper terminology or vision by nature to do the research on Google. Especially when I'm physically in the Main Land of China, where it takes some efforts to even get on Google, so doing code research took a lot of my time and was a little frustrating towards the end.

But again, the overall course and support are great! If this is not a 5 start course, I can hardly give out my highest mark to any other courses. It helped me to understand inferencial statistics, practice R, and think more like a statistician.

von Hao C

•Nov 06, 2019

Teaching: I really like the clear and concise teaching style of lecturer and the wide range of simple real-life example used to explain the course content.

I’m a social science student. Although I’ve studied quantitative research methods before, this course gives me some new insights into inferential statistics. I think I will never forget the statistical meaning of p-value after this course!

Course Structure: The course structure is well organized with clear focus in each week.

The first and second weeks are easy to follow, but the third and fourth weeks are more challenging.

Textbook: The textbook used in this course is a good supplementary material, although it is not necessary to read the textbook. Course videos have already explained everything that we need to know at intro level. However, it is worth reading the textbook for the third and fourth weeks.

Assessment: The assessment of quiz in each week is relatively easy. The exploratory data analysis required in peer-reviewed assignment is slightly challenging, because it might be hard for beginners to touch every required point.

von Tanika M

•Jun 12, 2020

I feel like I gained a solid foundation on inferential statistics from this course. I found the videos useful, with many well-explained examples. I would say that the readings should not be treated as optional - they were where I did the bulk of my learning. The scope of the final project is reasonable.

It may be relevant that I also took the previous course in this specialization, and I can see that not having done the previous labs would have made the project a little harder. As other reviews have said, the forums also seem much less moderated than the last course's.

von Jorge L

•Oct 20, 2016

Terrific course, i got here after starting the Data Science specialization on John Hopkins uni on Coursera, but there bit on statistics is awful, a waste of time.

I decided to give Courser another shot and definitely not regretting it, this course really go over the basics clearly and make sure to make enough exercise to revisit that clearly explain the fundamentals.

I was happy as getting to the final assignment i found myself doing quite an advance analysis and inference that i notice i really understood the topics on the course.

von 이제민

•Aug 06, 2016

It has a little expensive tuition fee than other courses such as Data Science (Johns Hopkins) and Data life (HarvardX_edx). But I decided this course rather than choosing the others because I felt that it was well organized and quite good supplements. What I like most about this course is instructor. She looks like enthusiastic to give a her idea and wisdom. It attracts me to take this course even though it is expensive relatively. Anyway, I appreciate her for dedicated teaching in advance.

von Kuntal G

•Oct 06, 2016

It is really the best Statistics course that i have ever done. After doing all the course in statistics i'm very much confident in statistics. The course and Specialization is very clear, concise, nice explanation with example videos to have better understanding of the theory. It is highly recommended course for anyone interested to learn statistics in their career. Please do the maximum the course in the specialization to have good grasp of statistics if you are beginner like me :)

von Emilio M

•Jun 05, 2020

Very concise and interesting. I was able to brush up many concepts. It is important to indicate to the students, that the materials provided are not enough to create a final project in a meaningful way.

This is because the code to use R is limited to the basics throughout the course. Extra or outside research is necessary to increase R skills.

Many students have technical difficulties, sometimes unusual. Is it possible to address them by expanding an FQA section?

von Dario B

•Nov 06, 2018

Very interesting material. Statistical inference was one of the great mysteries for me, and it is indeed a technical topic. But the professor does a great job in presenting the material in an intuitive way, giving an awesome introduction. Very interesting real examples too.

Looking forward to have a proof-based equivalent course, though maybe I should focus on a forma probability course first.

von Ondina F P

•May 17, 2019

Very good explained course, with lot of useful exercise, so you can be sure to understand the theory. Th practical examples in R are well designed and explained. This is definitely a must for someone interested in statistics, with beginning concepts that you need to keep in mind for further coursers. The teaches is also excellent, explanation and examples are very good. Recommended!

von John F W S

•Nov 05, 2016

I really enjoyed this course, it is pitched at just the right level for someone who is sometimes busy with part time work. It does ask that when you study, you study well. I've not learned any programming before these courses, so sometimes my knowledge of R is lacking. But it is rewarding to learn R to really see these statistical ideas come alive.

von Jose N d l R

•May 25, 2017

If you are new to this, get ready to sweat. This course teaches many many concepts and if you think that it tiptoes around it you will be surprised. You might walk away and forget some of the methods and tests since there are too many, but you won't get away without learning to interpret and reasoning absolutely everything that you compute or do.

von Jesus

•May 16, 2016

Great course, the professor is able to explain and articulate complex ideas into a digestible manner. If you ever taken a statistics class you know would know how incredibly rare it is to have such a great professor able to explain the material as well as she does. Thanks you very much Dr. Mine Cetinkaya-Rundel for teaching this course.

von Bruno A

•Mar 24, 2020

Nice refresher course on inference testing, with a broad coverage of the types of variables / analyses.

Not heavy at all on the math side.

Students have to find their tips for R-coding on the Internet for the most part. It is a good way to learn! But we could use more standard tips from the course itself, especially on EDA.

von Jacob T

•May 07, 2019

The best online course I have taken so far. It teaches you all the statistical methods you need to do for inference. The lessons are well taught and organized in a way where each lesson builds off the previous. The final project is also a great way to put everything you learned throughout together.

von Amarendra S

•Feb 26, 2019

Had a great learning experience with in depth knowledge of statistics, inference and hypothesis. Structure of the course helped me grasp things in an organized way. The use of real time data to explain concepts had a great impact in making things easier to understand and relate to things around us.

von José J P A

•Jul 04, 2016

Excelente curso. Vale totalmente la pena tomarlo. Es muy importante atender la lectura sugerida y tomar notas. Complementando la platica junto con la lectura sugerida estoy seguro que tendrás las herramientas necesarias para iniciar un desarrollo en el ámbito de análisis de datos.

von Praneeth K

•Apr 17, 2017

The course is structured very well and has some great content, suitable for anyone who is just beginning with statistics in R or if you want a refresher on statistics. Dr. Milne is a great instructor, i have taken some other courses of her's and was never disappointed.

von Lucía C

•Jun 09, 2020

Great course, really useful and amazing explanations by Dr. Mine Çetinkaya-Rundel. I learnt a lot and the data we are given to analyse in the final project is really interesting. Totally recommend this course to anyone interested in working with stats in R

von Thomas B

•Oct 31, 2016

Really good course on inference. The statistical tools and the reasons why those tools are used, are explained well. I am looking forward to the last week's exercise and the next courses of the series. This one is a bit more difficult than the first course.

von Bryan L

•May 11, 2020

The content of the course of was informative and clear. The lab sessions were really useful in evaluating one's understanding of the topic while introducing useful functions in R though more emphasis could have been placed on ANOVA during the lab sessions.

von Ako A A

•May 18, 2017

I found this course very exciting. The knowledge it imparts is so invaluable that I am keen to complete course after course. The lecturer also has a charm with which she holds your attention and makes learning quite a breeze. I give 5 stars unreservedly

von Muhammad F

•Apr 08, 2020

The course gives me an understanding of inference for numerical and categorical data. The example as well as the project assignment use real-world data which prepares the students to use the technique taught in the course to tackle real-world problems.

von Cynthia J J

•Dec 29, 2019

This is a wonderful course with a very good instructor. Her explanations and observations are clear, concise and on point. I am so glad I am taking this course because now the mystery of statistics is over for me. I finally understand this logic.

von Satoshi I

•Mar 17, 2020

This course is brilliant. It's straight forward and a lot but moderate practices. A quiz, working on R, and discussion forums assist your understanding of the contents. I am not a native English speaker, but I could enjoy this learning. Thank you.

von Patricia B

•Aug 04, 2017

This course is very complete. It helps, even who have already studied Statistics on university level before, to really understand the concepts on inference. The labs are cleverly built to help the student to use R and apply the concepts learned.

- Sinn und Zweck im Leben finden
- Medizinische Forschung verstehen
- Japanisch für Anfänger
- Einführung in Cloud Computing
- Grundlagen der Achtsamkeit
- Grundlagen des Finanzwesens
- Maschinelles Lernen
- Maschinelles Lernen mittels Sas Viya
- Die Wissenschaft des Wohlbefindens
- Contact-Tracing im Kontext von COVID-19
- KI für alle
- Finanzmärkte
- Einführung in die Psychologie
- Erste Schritte mit AWS
- Internationales Marketing
- C++
- Predictive Analytics und Data-Mining
- UCSD: Learning How to Learn
- Michigan: Programming for Everybody
- JHU: R-Programmierung
- Google CBRS CPI Training

- Natural Language Processing (NLP)
- KI für Medizin
- Guter Umgang mit Worten: Redaktionelles Schreiben
- Modellbildung von Infektionskrankheiten
- Die Aussprache des US-amerikanischen Englisch
- Software-Testautomatisierung
- Deep Learning
- Python für alle
- Data Science
- Geschäftsgründungen
- Excel-Kenntnisse für Beruf
- Data Science mit Python
- Finance for Everyone
- Kommunikationsfähigkeiten für Ingenieure
- Verkaufstraining
- Career Brand Management
- Wharton: Unternehmensanalytik
- Penn: Positive Psychology
- Washington: Maschinelles Lernen
- CalArts: Grafikdesign

- Zertifikate über berufliche Qualifikation
- MasterTrack-Zertifizierungen
- Google IT-Support
- IBM Datenverarbeitung
- Google Cloud Data Engineering
- IBM Applied AI
- Google Cloud Architecture
- IBM Cybersecurity Analyst
- Google IT Automation with Python
- IBM z/OS Mainframe Practitioner
- UCI: Angewandtes Projektmanagement
- Zertifizierung in Instructional Design
- Zertifizierung in Bauwesen und -management
- Zertifizierung in Big Data
- Zertifizierung Maschinelles Lernen für Analytics
- Zertifizierung in Innovation Management & Entrepreneurship
- Zertifizierung in Nachhaltigkeit und Entwicklung
- Zertifizierung in Soziale Arbeit
- Zertifizierung KI und maschinelles Lernen
- Zertifizierung in Räumliche Datenanalyse und Visualisierung

- Abschlüsse in Informatik
- Business-Abschlüsse
- Abschlüsse im Gesundheitswesen
- Abschlüsse in Data Science
- Bachelorabschlüsse
- Bachelor of Computer Science
- MS Elektrotechnik
- Bachelor Completion Degree
- MS Management
- MS Informatik
- MPH
- Master-Abschluss in Buchhaltung
- MCIT
- MBA online
- Master of Applied Data Science
- Global MBA
- Master in Innovation & Entrepreneurship
- MCS Data Science
- Master in Informatik
- Master-Abschluss in Public Health