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Introduction to Probability and Data

Introduction to Probability and Data

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8.6/10 (Our Score)
Product is rated as #17 in category R

This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes’ rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization. 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 concepts and techniques in this course will serve as building blocks for the inference and modeling courses in the Specialization. Duke University has about 13,000 undergraduate and graduate students and a world–class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.

Instructor Details

Mine Cetinkaya-Rundel is an Assistant Professor of the Practice at the Department of Statistical Science at Duke University. She received her Ph.D. in Statistics from the University of California, Los Angeles, and a B.S. in Actuarial Science from New York University's Stern School of Business. Dr. Cetinkaya-Rundel is primarily interested in innovative approaches to statistics pedagogy. Some of her recent work focuses on developing student-centered learning tools for introductory statistics courses, teaching computation at the introductory statistics level with an emphasis on reproducibility, and exploring the gender gap in self-efficacy in STEM fields. Her research interests also include spatial modeling of survey, public health, and environmental data. She is a co-author of OpenIntro Statistics and a contributing member of the OpenIntro project, whose mission is to make educational products that are open-licensed, transparent, and help lower barriers to education. She is also a co-editor of the Citizen Statistician blog and a contributor to the Taking a Chance in the Classroom column in Chance Magazine.

Specification: Introduction to Probability and Data

Duration

22 hours

Year

2016

Level

Beginner

Certificate

Yes

Quizzes

No

50 reviews for Introduction to Probability and Data

4.6 out of 5
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  1. Michael S

    The course lectures were very good and informative. However, this course does need some work. First, the text revision references were confusing. The homework assignments were a confusing as to where they should be performed; on our own or within GitHub. I have used R before and was using this course as a refresher. The course series definitely needs a optional introductory course in use of R, R Studio, GitHub, and R Markdown language. Similar to the JHU Data Science specialization. Finally, the course project was a bit deep for introductory Probability and Data. Need to make the course project less demanding or drop the need for a final course project until later courses

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  2. NGOUBOU N R L

    An excellent introduction to statistics. Recommend to everyone who wants to get into statistics

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  3. Yunjae C

    Good real world materials and insight teaching for understanding basic statistics. I recommend this course to everyone.

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  4. Alexander S

    On the whole I thought the theoretical content of the course was good, and that the supporting materials were quite helpful. I would strongly caution prospective students about the amount of time that is actually required to complete the course requirements. Specifically, I found that the amount of time that was, in actual practice, required to learn even the basics of R and to then apply this to actually doing the final assignment vastly exceeded the time suggested by the course instructions.

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  5. Yunkai C

    very helpful!

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  6. Erin A

    This course made principles of probability interesting, going beyond the usual examples of coin flips, dice rolls, and card draws. The discussion about the limits of which observed trends can be applied to a greater population of interest was clear and the project gave us an opportunity to put it into practice ourselves. I especially liked the opportunity to ask questions of a large dataset and generate tables of data and graphs to illustrate these tables a bit more clearly. I feel I now have a good foundation upon which to build!

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  7. Natalia V C M

    The course is really good, thank you so much for your work. I just would like that there would be available corrections for the bad answers in the quizzes, to know what we did wrong and learn, also I would like to receive an evaluation of someone of the teachers in the final lab, not only of my classmates.

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  8. Mariliis J

    This course was planned very well. It covers topics multiple times but in different forms/approaches, which makes the material easy to learn and obtain. Furthermore, the practical exercises and coding lab were guided enough yet let the learner have independence as well in the solutions.

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  9. Majeed K

    This was a nice and informative course

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  10. Francisco M

    Excellent course, very informative

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  11. Valeriy K

    I couldn’t be more happy with this course. Super rich course materials, diverse tasks, hands on labs, and many more. I really love the textbook, Open Statistics the best statistics guides I’ve seen so far. Huge thanks to the professor Cetinkaya Rundel!

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  12. Natasha S

    Peer reviews were overwhelming

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  13. ALOK P S

    course was very helpful for the begginers

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  14. Goyani Z H

    a very useful course for beginners. Proper instructions are given by the instructors.

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  15. Nitin P

    This course is a good starting point for someone to learn probability concepts.I really enjoyed this course along with e textbook. Thanks Coursera.

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  16. Zhang R

    This course helps me a lot to build a basic understanding of statistics knowledge in probability and data. I am looking forward to continue this series of courses in the future!

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  17. Shiyue L

    The data material choose is not good enough, there various of the problem in the process of draw graph, due to the data quality.

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  18. Hao C

    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, given I’ve studied quantitative research methods before, this course is easy intro to and good refresher of data and probability theory. This course really gives me some confidence to continue to study probability theory, after finishing this specialization. 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. The textbook also covers some extra optional topics that are worth reading. Course Structure: The course structure is well organized with clear focus in each week. Assessment: The assessment of quiz in each week is relatively easy. The exploratory data analysis required in peer reviewed assignment is relatively difficult for beginners. However, the course mentor has drafted an easy to follow guide in the discussion section which is really helpful for finishing this assignment.

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  19. MAYANK N

    good

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  20. Dhruv C

    good

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  21. Ding W

    wonderful and so interesting

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  22. Shitao L

    A very good course! Basic and detailed

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  23. Aaradhya G

    Absolutely amazing! It is clear that the professor, Ms. Mine Cetinkaya Rundel is passionate about the subject and knows it inside out. The practical example based approach to learning is appreciated, since a lot of statistics courses don’t give learners a realistic setting to think about their knowledge, leaving them with the infamous ‘how will this help me in real life?’ question. The book, OpenIntro is also very helpful in this regard. The R course has been introduced nicely too. The difficulty curve might take time to get used to, but the packages introduced and the codes used make sense, so it should not take too much time. Wholeheartedly recommended!

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  24. Ian G

    Great course.

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  25. Hasan A

    A well thought course organized in a perfect way. Thank you very much!

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  26. Chuwen Z

    Very useful, especially in R. I really like the final project since it really gave me the opportunity to explore the dataset on myself. it was a little bit challenging for me since I had to integrate all of knowledge I learned here. But I have to say it is really useful. The narrator is brilliant too. Each concept and statistic method is clear and acceptable.

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  27. SHEN Y

    Very clear and interesting. Every learning point comes with a vivid example.

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  28. Shrayan B

    Great course for beginners.

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  29. Gaurav P

    Excellent techniques and methods involved in this scores. Learnt a great deal in R and doing analysis with hand on project was a great experience

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  30. Khaled A I

    The course is very organized and informative. explanation is very clear. the only issue is that the final project requires R skills that are not taught during the course. The labs during the course is extremely primitive compared to that project

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  31. SHUANGSHUANG L

    Overall i found the R programming really useful and i would love to learn more about it.

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  32. Harshit A

    Very well structured course and gives a headstart if one wants to go in Data analytics or Data Science. All topics are explained in the easiest way possible.

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  33. Volodymyr F

    Thanks for the excellent course. The whole “Statistics with R” specialization is a perfect introduction in statistics.

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  34. Khawaja M O

    BEST

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  35. MOHAMMAD R W

    The best course for statistics

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  36. Eduardo B D S

    Excellent course. Gave me the necessary foundations to understand statistics and to use R as a usefull tool.

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  37. Alicia G

    Very useful!

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  38. Christopher S

    This course had a good balance of easy and challenging content. I like how the reattempt feature of the quizzes doesn’t just give you all the same questions again in a different order. But at the same time it doesn’t completely change the set of questions. This forces you to go back a really understand the content if you want to maximise your mark. The final project seemed harder than I was expecting, but that resulted in gaining a lot more practice with RStudio, which really helped to learn it well.

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  39. Josy D O V

    very well conducted. Brings many real example of how to apply the statements. Very weel done. I recommended!!!

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  40. FLAVIA N L A

    Excellent course. Classes were intense and the professor was very didactic. It took me around 10 hours a week of dedication, and the Final Project of the last week required around 40 hours of work. I am very pleased with the final result, but I think it is important to let it clear the real time expected of effort here. Unless you are already really familiarized with the concepts and with the R platform, the course requires a strong commitment. My final verdict: I am very grateful to have done a course of this quality from where I am. Thank you: professors, mentors, developers and fellow classmates! Every minute of my time was worthwhile with you.

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  41. Bernardo E

    Everything goes smoothly but the last assignment: it’s crazy difficult. Every week is a guided exercise but the last one has very few related to that. 2 stars out of 5 because nonetheless the probability part is interesting and well explained. I didn’t finish the course because it was too hard for me to fill the assignment. I paid 44Euro(s)/month and the second month i decided to give up in order to save money it would require me at least another month (they say 2h in total..). Don’t do it unless you have a prior solid knowledge of R.

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  42. Bryan L

    This is a useful statistical course for anyone who seeks to gain a basic understanding of probability. The R coding assignments are especially useful but one could benefit more if they already knew how certain functions works in R. The dplyr package is especially emphasized and I suggests going to Youtube to know the main functions that are used for data wrangling.

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  43. Emmanuel E

    Wow, I would totally recommend this course to just about anyone but mainly to those seeking to have a thorough grasp of Probability and Statistics.

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  44. Leon M R

    Through this course I finally got to understand R as a whole. It was also possible to begin to understand how language works. The course is quite didactic, but requires some familiarity with basic statistical concepts and data visualization, which I noticed especially from the projects I evaluated.

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  45. Hassan A

    Excellent course. it provides a solid foundation to build upon for later statistics learning.

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  46. Rohit D W

    It was really a great course, on an initial basis, you will learn different things a lot. And as a statistics student, I enjoyed the coursework, with an r programming language it was different at first but while getting used to it, it’s a nice and easy way to deal with data.

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  47. Yash G

    Good course for statistics but not for R

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  48. Nicholas J

    This is a very good introductory course!

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  49. John H

    The instructions for the final project need to be much clearer. I had a hard time figuring it out, and all of the projects I peer edited were done poorly. Otherwise, I enjoyed the course very much!

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  50. Muhammad F

    The course give me a basic understanding of basic statistics and show me how to employ statistical calculation and visualization by using R studio. One of the most exciting things is the project assignment which analyzes real world data.

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