Course Details
Cost
FREE
Upcoming Schedule
- On demand
Course Provider
Coursera online courses
Coursera's online classes are designed to help students achieve mastery over
course material. Some of the best professors in the world - like neurobiology
professor and author Peggy Mason from the University of Chicago, and computer
science professor and Folding@Home director Vijay Pande - will supplement your
knowledge through video lectures. They will also provide challenging
assessments, interactive exercises during each lesson, and the opportunity to
use a mobile app to keep up with yo...
Coursera's online classes are designed to help students achieve mastery over
course material. Some of the best professors in the world - like neurobiology
professor and author Peggy Mason from the University of Chicago, and computer
science professor and Folding@Home director Vijay Pande - will supplement your
knowledge through video lectures. They will also provide challenging
assessments, interactive exercises during each lesson, and the opportunity to
use a mobile app to keep up with your coursework. Coursera also partners with
the US State Department to create “learning hubs” around the world. Students
can get internet access, take courses, and participate in weekly in-person
study groups to make learning even more collaborative. Begin your journey into
the mysteries of the human brain by taking courses in neuroscience. Learn how
to navigate the data infrastructures that multinational corporations use when
you discover the world of data analysis. Follow one of Coursera’s “Skill
Tracks”. Or try any one of its more than 560 available courses to help you
achieve your academic and professional goals.
Provider Subject Specialization
Humanities
Sciences & Technology
Course Description
Statistics One is a comprehensive yet friendly introduction to statistics.
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- 1 review
- 1 completed
7 years, 2 months ago
Might possibly be worth doing in another presentation, if they fixed the
problems, but the first was disappointing. It was marred by very poor
organisation and attention to detail. For example: in several different pieces
of work, the automatic grading system marked correct answers wrong. In one
case this was eventually corrected but the correction introduced a new error!
The course team did not make effective use of the Announcements page or the
official course forums so students were left in the dark about what was going
on. I gave up doing the assignments. The lectures were OK, but not great, in
my opinion. Overall problem seemed to be confusion about who the course is
for. It's advertised as being for complete beginners, and the lectures do
start very slow (but never actually explain what kurtosis is...), but at the
end the pace is hugely faster and material is included that seems too advanced
for a short intro stats course and w...
Might possibly be worth doing in another presentation, if they fixed the
problems, but the first was disappointing. It was marred by very poor
organisation and attention to detail. For example: in several different pieces
of work, the automatic grading system marked correct answers wrong. In one
case this was eventually corrected but the correction introduced a new error!
The course team did not make effective use of the Announcements page or the
official course forums so students were left in the dark about what was going
on. I gave up doing the assignments. The lectures were OK, but not great, in
my opinion. Overall problem seemed to be confusion about who the course is
for. It's advertised as being for complete beginners, and the lectures do
start very slow (but never actually explain what kurtosis is...), but at the
end the pace is hugely faster and material is included that seems too advanced
for a short intro stats course and wasn't really grounded properly. In
practice, a high proportion of students on the course (who were still there a
few weeks in) seemed to have taken stats courses before, or even taught them.
Student
10/10 starsCompleted
4 years, 11 months ago
I needed to learn basic stats, and R. I love how this course is just that. I
went away from this course being able to process the results of my study in R.
I really liked the video tutorials because Conway went through the output and
explained each step. This gave me intuition to be able to understand the
output when I ran my stats. I wish there were more stats courses offered by
this university and teacher.
- 16 reviews
- 16 completed
5 years, 7 months ago
I really enjoyed this class. I think the professor does a great job of
presenting the material. I took this class in its first iteration and the only
negative thing I have to say is about the student community. At that time, the
forums were overshadowed by people who seemed to have some kind of personal
vendetta against professor Conway. It was really sad to see. There is a
programming tool called 'R' that you will need to learn. It is very easy to
learn. It is used by statisticians all over the world. I think too many people
didn't have an understanding of the mathematics and other skills needed for a
statistics class. (even an introductory one) Having said that, I think this
was a great introduction to statistics. I like the real world examples he
used. I would recommend this to everyone.
- 9 reviews
- 7 completed
5 years, 9 months ago
Overall I thought it was very good. I took statistics many years ago so this
was a good way to refresh my knowledge on the subject. My only "complaint" is
that some of the lab exercises felt a little disconnected from the lectures,
where we had to take extra steps that were not mentioned in the videos in
order to solve the problems. Anyway, I really did like it and would take
further courses on the subject if they were offered by Prof. Conway.
- 1 review
- 0 completed
6 years, 2 months ago
This is my 10th or so course and my 4th statistics course on Coursera after
"Computing for Data Analysis", "Data Analysis", "Mathematical Biostatistics
Boot Camp 1" I got the maximum score for all assignments and 24 out of 25 at
the midterm. However this is the worst class I took on Coursera and here's
why: The material is dense but fails to properly cover the basics and merely
glancing through them. The homeworks are very easy and don't require a proper
understanding of the material. Out of 10 questions sometimes you can do them
all mechanically without having to understand much. Also it's not uncommon to
have 3 different, yet semantically identical questions such as 1\. what is the
covariance between x and y 2\. what is the covariance between x and z 3\. what
is the covariance between y and z However even though the homework takes about
10-30 minutes to complete (sometimes less than 10). It may take another 30
minutes to figure out...
This is my 10th or so course and my 4th statistics course on Coursera after
"Computing for Data Analysis", "Data Analysis", "Mathematical Biostatistics
Boot Camp 1" I got the maximum score for all assignments and 24 out of 25 at
the midterm. However this is the worst class I took on Coursera and here's
why: The material is dense but fails to properly cover the basics and merely
glancing through them. The homeworks are very easy and don't require a proper
understanding of the material. Out of 10 questions sometimes you can do them
all mechanically without having to understand much. Also it's not uncommon to
have 3 different, yet semantically identical questions such as 1\. what is the
covariance between x and y 2\. what is the covariance between x and z 3\. what
is the covariance between y and z However even though the homework takes about
10-30 minutes to complete (sometimes less than 10). It may take another 30
minutes to figure out what the format is for some of the answers. It can be so
frustrating it feels like a bad joke. Sometimes you have to write integer
values, sometimes 2 decimals rounded values, but it won't accept them unless
you type them in a particular format (which is not explained). For example in
the same assignment an answer needs to be formatted as "0.19" and anther
answer needs to be ".19", just because. Also these rules seem to be changing
between assignments. The forums have more questions/comments about answer
format than for the actual assignment. Here's an example "I feel like every
time there was a confidence interval question, there was a different format. I
got 8 points from 2 attempts and then lost another 5 trying to guess the
format until I came here. Was it so difficult to let us use any format we want
and then check that our result is within a certain error range? Coursera does
stuff much more complex than this at other courses. I am disappointed." "Quiz
7 Q4 & 5, Q6 & Q7 format" had 68 questions/comments when I wrote this
(https://class.coursera.org/stats1-002/forum/thread?thread_id=2180) and there
were other parallel threads.
- 1 review
- 0 completed
6 years, 2 months ago
I was very excited about the course when I first saw the syllabus. The reason
was the coverage of the topics. It starts from very basics and attempts to
teach advanced topics through the course. However, as the course proceeds, I
realized that the attempt of covering large number of topics is actually a bad
idea. Since the course attempts to cover too many topics in 3 months, the
lectures were not in depth at all. It is a statistics course, with just a few
slides with formulas. Some people may think that it is something good, but I
think otherwise. Dr. Conway tries to explain ideas too "intuitively". The
statistical methods were not explained in depth at all. The slides are not
useful, especially for self-study. Unfortunately, the labs was not good
either. I see the difficulty of teaching statistics and programming language
for practice at the same time. Since the concepts were not covered enough in
the lectures, most weeks, using R ...
I was very excited about the course when I first saw the syllabus. The reason
was the coverage of the topics. It starts from very basics and attempts to
teach advanced topics through the course. However, as the course proceeds, I
realized that the attempt of covering large number of topics is actually a bad
idea. Since the course attempts to cover too many topics in 3 months, the
lectures were not in depth at all. It is a statistics course, with just a few
slides with formulas. Some people may think that it is something good, but I
think otherwise. Dr. Conway tries to explain ideas too "intuitively". The
statistical methods were not explained in depth at all. The slides are not
useful, especially for self-study. Unfortunately, the labs was not good
either. I see the difficulty of teaching statistics and programming language
for practice at the same time. Since the concepts were not covered enough in
the lectures, most weeks, using R to practice concepts discussed in the
lecture was like black magic. Just call the function that is asked, find the
number in the output and that's it. Towards the end of the course, it became
obvious to me. Finally, I realized that I don't learn anything anymore and
decided to drop the course.
- 33 reviews
- 27 completed
6 years, 2 months ago
Since i do have some familiarity with Statistics, the syllabus looked good.
But the student has to learn the "R" programming system at the same time as
he/she is absorbing the concepts and doing the calculations. Course would be
better if a week or two were devoted to learning the R programming system, but
the course is already rather lengthy as it is. Definitely NOT "friendly".
- 3 reviews
- 1 completed
6 years, 2 months ago
I am really enjoying this class, and would recommend it to anyone looking to
learn statistics. I am concurrently enrolled in Calculus, and I find
comparisons of these two classes interesting. I find the professor very
engaged and working very hard to provide excellent teaching. The material is
well thought out and clearly presented. It looks to me like there are
challenges for a statistics teacher that are different from those faced by a
calculus teacher. The repetition of calculating calculus problems provides a
sense of "learning the material" for me that I don't feel as strongly in this
course. The weekly labs in R are great; I just think it is harder to master
the material when you are "evaluating output." There are two minor issues I
have with the class, and they are really just personal preference. First, the
professor stays away from greek symbols opting instead for abbreviations such
as SD for standard deviation. The second i...
I am really enjoying this class, and would recommend it to anyone looking to
learn statistics. I am concurrently enrolled in Calculus, and I find
comparisons of these two classes interesting. I find the professor very
engaged and working very hard to provide excellent teaching. The material is
well thought out and clearly presented. It looks to me like there are
challenges for a statistics teacher that are different from those faced by a
calculus teacher. The repetition of calculating calculus problems provides a
sense of "learning the material" for me that I don't feel as strongly in this
course. The weekly labs in R are great; I just think it is harder to master
the material when you are "evaluating output." There are two minor issues I
have with the class, and they are really just personal preference. First, the
professor stays away from greek symbols opting instead for abbreviations such
as SD for standard deviation. The second issue is that all of the data appears
to be made up. With all the open data, it would be more engaging for me to
work with real datasets. I love the class tho and recommend it highly -
particularly for someone looking for a review of statistics or a second look
at the material with an R perspective.
- 6 reviews
- 5 completed
7 years ago
Presentation and organization of the lectures was fine. Sometimes it lacked
some precise definitions, but the key topics were well explained. Working in R
was almost not explained at all, only examples of how to solve some very
specific tasks. Anything else was left to the student to find out. That's OK
for me as a programmer, it's what I do every day, but for other people it may
be more annoying. What was really disappointing was the interactive parts of
the course. Quizzes where you wouldn't see if you answered correctly or what
was wrong with your answer. Sometimes even the marking was plain wrong. How
does that help learning? (I believe that should be the main benefit of
quizzes, not the grades) None of the staff were active in the discussion
forum, only later I found that there was some facebook group (created by
students) where staff replied from time to time. What's the point of having a
discussion forum, then? In the end, I'v...
Presentation and organization of the lectures was fine. Sometimes it lacked
some precise definitions, but the key topics were well explained. Working in R
was almost not explained at all, only examples of how to solve some very
specific tasks. Anything else was left to the student to find out. That's OK
for me as a programmer, it's what I do every day, but for other people it may
be more annoying. What was really disappointing was the interactive parts of
the course. Quizzes where you wouldn't see if you answered correctly or what
was wrong with your answer. Sometimes even the marking was plain wrong. How
does that help learning? (I believe that should be the main benefit of
quizzes, not the grades) None of the staff were active in the discussion
forum, only later I found that there was some facebook group (created by
students) where staff replied from time to time. What's the point of having a
discussion forum, then? In the end, I've dropped the course after some six
weeks because I simply had better things to do.
- 1 review
- 1 completed
6 years, 11 months ago
Great course! Although it may not be actually for someone without any
background in statistics or programming, it was very enjoyable for me with a
very basic background in statistics (i had taken a couple of courses in my BS)
and some programming during highschool using visual basic and delphi, neither
of them are like R o Pyhton but taught me the rigorousness of syntax and
semantics in programming. Strictly talking from the course at the end it was
too much info but still was manageable. Maybe it was a bit tedious to know all
the background from the examples used for statistical analysis (like the
history of a basketball player or salaries in certain departments of the
university) but in the end of the analysis that background made more clear and
important the numbers that such analysis gave pointing out to much real
conclusions and making better examples. In my belief the course would be
better if it had more time (either from the ...
Great course! Although it may not be actually for someone without any
background in statistics or programming, it was very enjoyable for me with a
very basic background in statistics (i had taken a couple of courses in my BS)
and some programming during highschool using visual basic and delphi, neither
of them are like R o Pyhton but taught me the rigorousness of syntax and
semantics in programming. Strictly talking from the course at the end it was
too much info but still was manageable. Maybe it was a bit tedious to know all
the background from the examples used for statistical analysis (like the
history of a basketball player or salaries in certain departments of the
university) but in the end of the analysis that background made more clear and
important the numbers that such analysis gave pointing out to much real
conclusions and making better examples. In my belief the course would be
better if it had more time (either from the course as from the students) to
explain the topics with more fundamental principles and more examples (being
this the reason why I don't rate it with 5 stars). Finally I strongly
recommend this course to anyone who wants to learn statistics and has at least
barely knowledge of the theme and patience to learn R.
- 8 reviews
- 7 completed
6 years, 12 months ago
I had to drop out, partly because I joined the course in the middle and
already missed deadline. I was also taking 3 other courses, so had to drop
this one out. Having said that, the instructor is passionate about the
subject, and I was able to digest the content until the half way through. I
would take it again when I find more time (though new courses are keep popping
out, so probably never have enough time ....
- 2 reviews
- 2 completed
7 years, 2 months ago
I actually don't agree that this class was "designed to be a friendly
introduction to fundamental concepts in statistics". The lecture on
descriptive statistics even states that it should be review. That doesn't mean
it was a bad course. I should probably mention that it covered mostly
inferential statistics and barely mentioned probability at all. Learning R was
very cool. I put a lot of time into it and got a lot out of it although the
mixed factorial anovas at the end almost killed me. Good class. Highly
recommended!
- 2 reviews
- 2 completed
7 years, 2 months ago
I learned a lot, some of the things were clarified, but many still confusing.
And it was a little slower. Also that R... I did all my assignments in Excel.
But still, it's a nice one.
- 19 reviews
- 16 completed
7 years, 2 months ago
Excellent content and outstanding teacher. However, what misses (in my view)
to be perfect is the style - a bit too oriented towards the classic teaching
(relatively long chunks of lessons, a bit too much emphasis on the formal
testing on the concepts instead of the practical aspects of the craft, etc.).
- 2 reviews
- 2 completed
7 years, 2 months ago
It was an wonderful experience with Statistics one. This course helped to
learn some basics of R, interpretation using R. I will be eagerly waiting for
Statistics Two.
- 25 reviews
- 25 completed
7 years, 3 months ago
I studied Stats way back when and never fully grasped it. This well thought
out and brilliantly executed course changed all that. First rate!
- 4 reviews
- 4 completed
7 years, 3 months ago
The first part of the course was great. At the end the pace was too fast. Has
potential to be a great course in statistics.