Inferential statistics are concerned with making inferences based on relations found in the sample, to relations in the population. Inferential statistics help us decide, for example, whether the differences between groups that we see in our data are strong enough to provide support for our hypothesis that group differences exist in general, in the entire population.
We will start by considering the basic principles of significance testing: the sampling and test statistic distribution, p-value, significance level, power and type I and type II errors. Then we will consider a large number of statistical tests and techniques that help us make inferences for different types of data and different types of research designs. For each individual statistical test we will consider how it works, for what data and design it is appropriate and how results should be interpreted. You will also learn how to perform these tests using freely available software.
For those who are already familiar with statistical testing: We will look at z-tests for 1 and 2 proportions, McNemar's test for dependent proportions, t-tests for 1 mean (paired differences) and 2 means, the Chi-square test for independence, Fisher’s exact test, simple regression (linear and exponential) and multiple regression (linear and logistic), one way and factorial analysis of variance, and non-parametric tests (Wilcoxon, Kruskal-Wallis, sign test, signed-rank test, runs test)....

MN

2020年7月24日

Feeling blessed to perform this course . It was truly an amazing experience for me to go though this course .Learned bunch of theories with their mathematical example.Thanks to the instructors.

ND

2018年2月12日

Incredibly dense (which they warn you about) so the lecutres fly over so much important info it's hard to keep track of even with a strong focus. A very good overview though.

篩選依據：

創建者 Scott A H

•2017年1月3日

I found the course was very confusing and the language used in the quizzes and exams didn't always match the language used in the lessons making it very difficult to understand what was wanted.

For a non-specialist, statistics is almost always a struggle, intently making it more difficult by trying to use trick questions and application in the quizzes and exam beyond what was covered in the course makes it really really difficult for those of us who are naturals at math.

I worked really hard in the course and finally made it thought all 6 weeks of the course but after one try at the final exam I said to myself enough is enough. I hate being a quitter, but I was not learning statistics and causing myself many headaches and feelings of inferiority and self-doubt because I just couldn't match the quiz and exam questions to the material covered in the course.

Maybe other people are much smarter than I am, but this source was a soul and time killer for me.

創建者 Ute T

•2019年3月13日

Week 1 to Week 5 were well explained, however the quality of the videos declined steadily to the end of the module. Many inconsistencies between video - audio - written text.

Most upsetting was quality of Week 6. In comparison to the parametric statistic parts which were super well organised, structured in assumption - hypothesis - test statistic and anything else important, the Week 6 was terribly confusing. It did not contain the most important formulas and explanations (I was researching online on other fora to reply to the quizz). I suggest a full review of non-parametric statistics, as it is an important chapter for many social scientists working with smaller sample research. I really think this has been neglected over the previous parts.

Also in comparison to Module of Basic Statistics, this one has not had a great quizz section. There are no hints of what might have gone wrong when answers are wrong, so the learning effect is 0 if we get answers wrong.

創建者 Markus W

•2016年5月15日

For someone who is not familiar with inferential statistics, this course is too compact. I lost the overall picture: it seems that a dozend methods were introduced, but I failed to understand under which preconditions each method is deployable. I am confused.

創建者 Grace L

•2018年7月8日

I don't feel the videos were sufficient enough to teach the methods for working through the formulas or to efficiently identify which scenario a certain formula was to be applied. The quiz instructions were vague and it was extremely difficult to know exactly what was being asked or which formula to apply. Often I had to result in giving my best guess. Forums were not helpful. Most questions were two years old or a few months old at the earliest and answers were not helpful. This course is especially confusing for beginners. I don't see how people have actually been able to learn from this course. With Basic Statistics course I at least felt I got a good basic understanding of the material. This course went miles over my head.

創建者 Sara J

•2019年5月16日

Terrible confusing questions in final... never take this if you are a beginner!

Incredible to see I am passing all quizzes and R labs given the lack of supervision and guidance from professors (this is after I have consistently sent emails and asked for extra help).

PLEASE revise this whole course for the sake of education.

創建者 yongbin z

•2016年4月14日

I understood inferential statistics better with this course. Both teachers made the concepts clear for me. The R homework helps me review inferential statistics methods.

創建者 Tay J

•2017年8月7日

While I appreciate the staff's efforts in making this MOOC and would love to thank them with five stars, I decided to give an average rating. I feel like too much material was packed in short lectures so that it is almost impossible to understand them fully (it gets increasingly so after week five). Oftentimes new concepts are explained and gone within seconds, and it largely comes down to memorizing formulas rather than understanding them. It seems like the lecturers were reading off a script that does not necessarily take into consideration the capacity of a student who just began learning inferential statistics.

I don't know - if one is already somewhat familiar with the materials or a genius then he or she may not have a problem following the course. But I, having had a reasonably good knowledge in basic statistics before the start of this course (obtained good results in both offline and online upper-secondary school-to- elementary freshman level basic statistics courses), frequently had to watch other MOOCs (e.g. there is a great course on inferential statistics on Khan Academy - longer videos for the same topics but they let you grasp the principles firmly) because I simply did not find the course videos sufficient.

On the positive side, I found the R-labs helpful. On top of that, quizzes and exams were quite difficult for a MOOC, which sometimes caused frustrations but still forced you to put a significant effort to learning.

On the negative side of the difficulty, sometimes I was stuck with utterly no way to proceed in the quizzes. Forums are not very active. Because the lectures are short and packed with content, they often did not contain any hands-on problem-solving procedures, and the student is left with abstract concepts and formulas at the quizzes. From time to time there are errors in the video graphics or quiz questions.

In the end, I did pass the course with about 94% final grade. However, I feel like I could have saved some time and frustration had the concepts been explained in more detail in a more learner-friendly manner and if there was a way to get some guidance (like hints) when stuck at certain quiz questions.

創建者 Do H L

•2016年9月3日

This course is awesome on so many levels. This is the best inferential statistics course I've come across. Here's why:

*** The slides are beautiful and visually appealing, making following the rigorous content easier to digest.

*** Instructors are captivating and articulate, the explanations are clear and concise.

*** The assignments are very very tough, making the course incredibly challenging, but worth it. Honestly, I don't get why people give 1 star because the course is tough. This should be a huge plus.

It was a real challenge getting 100% for everything. For every quiz, I attempted 2 - 3 times to get 100%. The challenge is worth it. I couldn't thank you enough for this course. You explain tough statistical concepts like the difference between prediction intervals and confidence intervals really well. Also, I think this course has the best teaching for Analysis of Variance (I have taken a few other statistics moocs). Also, your course helped me appreciate the meaning of R-squared, standard errors, confidence intervals in a very intuitive fashion. There are many other new things I've learnt from your course, some of them I thought I knew, but you helped me to either "Aha" or understand them more deeply.

Before this course, most of the time statistics to me is like plug-and-play using procedures and and softwares. But now, I can understand the concepts and what the calculations really mean.

Thank you for creating quizzes that make us really do step-by-step calculations and not just plug data into equations to get results like so many other statistics moocs do.

The pedagogy is really great. Sometimes quizzes can be frustrating because I need to read very carefully into the meaning of the questions and all the options. However, the learning experience is really worth it.

Again, thank you for an amazing course! This is rare stuff!

It is without a doubt, a lot of passion and effort has been put into this course and this series.

創建者 Zainab H

•2018年10月25日

This course was relatively difficult for my slow brain. I learned A LOT. but I still feel the need for doing this course one more time

創建者 Yanbing S

•2019年6月2日

It's good for a person who needs a certificate urgently. But not good enough for someone who wants to master the subject.

The course is very rigorous in terms of the depth and width of the content. But for the later weeks, the videos were so succinct that many details are not explained well. For a beginner, this is apparently insufficient. I had to look it up on other websites to know what they are talking about (I also wished they had recommended a textbook). Also, the lack of practices also makes the course less valuable for someone who wants to actually be good at it.

創建者 Syberen v M

•2019年4月7日

I took this course as a follow up to "basic statistics". The course is dense and fast-paced, so that's something to prepare for. Here are my observations:

The good:

The R labs are a lot better compared to basic statistics, where they were a disaster. You'll put to use the built-in functions in R to calculate your results.

Also the general amount of information is nice, I feel like I learned a lot about inferential statistics.

The bad:

Sometimes the videos are too fast, functions are shown for 2 seconds not allowing time to absorb the material. I often have to go to other sources to clarify what was meant.

Also frustrating is that there's no feedback on the exams, you're left to guess what you did wrong. Multiple times I found out that it was a rounding error, but the amount of digits are not specified in the question, so you have to re-take the exam several times until you find the expected amount of digits.

Finally, some of the required formulas are not included in the "formulas and tables" document. I hope this will be fixed, since this is essential to passing the course successfully.

創建者 Patrick C

•2020年3月28日

I felt this course was educational and worth the effort.... BUT it was effort. The lecture progressively got more difficult to tease out the necessary nuggets of info for the exams.. Glad its over...Would not like to do it again

創建者 Gerard Y

•2018年7月13日

A pity: the learning objective is really interesting, but the course quality does not live up to expectations. Teachers rush too fast into videos, without taking time to elaborate on terms used in formulas, elaborate with one example, explaining pitfalls, or explaining how we should do things in practice (for example in relation with statistical software). Examples lack variety: I liked the videos on Chi-Square test which used a different analogy with paintings. Variations on cats statistics tend to blend together in memory, and be less efficient. There's also a lack of written textbook that we can consult as a reference. The tables and formulas pdf file is a start, but is lacking many formulas and tables, explanation of data used in formulas; some sections are not even in English. Last point (I keep the positive at the end), the codecamp was really good overall.

創建者 Elpida S

•2018年7月17日

First of all, it is a very demanding course. I claim that it could not be easy for everybody to complete it especially in the field of Social Sciences. Secondly, we must attend a lot of material. Both quiz and assigments are so challenging. That means that is a very stressful proccess, each of us should devote so much time in order to keep up with the deadlines. Moreover there are a lot of theoritical videos , a lot of types, of course is very difficult to put into practice.. All of the learners have busy life ( I suppose) and this course really does not help at all.

創建者 Jackson H

•2017年10月7日

Videos have massive typos in equations, quizzes are never clear as to how many decimal places they want (sometimes 3, sometimes 4, sometimes rounded), and quizzes require you complete problems but provide no examples in the videos.

創建者 Soh W K

•2020年5月13日

Inferential Statistics, probably the most important course which I had taken in my lifetime, and it's pretty difficult. However, the reward is a sense of achievement that after you gone through the grueling course syllabus, and passed the course, with all your own calculations, and own understanding, you will know that you had become a qualified entry level RESEARCHER. If getting a Masters or PhD. is your dream in life, this course is highly recommended to gain a length & breath & deep understanding of Inferential Statistics!

創建者 Arman B K

•2018年11月13日

Completing this course requires perseverence but it is 100% worth it. There's a lot of material covered and the videos simply provide signposts for the topics but one doesn't learn statistics by watching videos. The real learning takes place during quizzes and assignments. The final exam is time consuming and tough and students need to truly master the material to earn a high grade.

創建者 Nicholas D

•2018年2月13日

Incredibly dense (which they warn you about) so the lecutres fly over so much important info it's hard to keep track of even with a strong focus. A very good overview though.

創建者 Pankaj A

•2017年7月4日

Hi, I enjoyed really well and this very good course on Inferential Statistics. My experience was really good. Thank you for providing the course for free!

創建者 Thanh H T

•2017年11月23日

Great!! I've completed. Its quite hard initially but it would be pretty easy if you read given Formulas table. Trust me!!

創建者 Muhammad A R

•2018年12月28日

loved the way, you carried a statistics virgin like through the course

創建者 Lyra F

•2019年7月14日

The course helped me learn the main tenets of applied inferential statistics (I see it as applied because not much mathematical explanation on how the formulas came about here). Although my execution of statistical tests is not perfect by the time I completed it, I have largely understood what tests to use in what circumstances and to analyze problems in a statistical way. I appreciated Anne-Sylvie's clear delivery and the effective visuals in the videos. Without the visuals, it would have been hard to keep up with the pace of the course. The one star off is for the occasional confusion in delivery and questions in the final exam.

創建者 Marcelo B

•2019年10月17日

Excellent course content. The only thing to improve is the statistical package (You could teach SPSS) and the evaluation process (Some questions are intended to deceive rather than to evaluate learning).

創建者 Donald M

•2018年4月15日

Much more study required than the Basic Statistics course, I completed with 93% by using a notepad, pausing regularly and taking a lot of notes.

創建者 Jose M P

•2020年7月17日

The previous course (Basic Statistics) was way better at explaining subjects and what the mistakes where in tests. This made it easier to learn than this course which was way more complicated and strict in their questions. I ended up not understanding some subjects entirely but also I don't understand what is it that I got wrong. Maybe there are ways to find out but I barely had time to complete the course so I had even less time to do a thorough research on every mistake I had. Just wished this was easier.

Also, there are some mistakes with what the teachers are saying and the numbers in the videos. Normally I would just understand it as an honest mistake, but I noticed people made remarks on this 2 years ago or so and they haven't been fixed. This makes me feel like the University of Amsterdam doesn't really care about the quality of this course.

In conclusion, subjects are very interesting and if you have the time to really dig into the course, it is ok. But because I paid a monthly fee, I expected it to be of far better quality and more student friendly and not just an old fashioned course where you have to get by on your own.

- Finding Purpose & Meaning in Life
- Understanding Medical Research
- Japanese for Beginners
- Introduction to Cloud Computing
- Foundations of Mindfulness
- Fundamentals of Finance
- 機器學習
- 使用 SAS Viya 進行機器學習
- 幸福科學
- Covid-19 Contact Tracing
- 適用於所有人的人工智能課程
- 金融市場
- 心理學導論
- Getting Started with AWS
- International Marketing
- C++
- Predictive Analytics & Data Mining
- UCSD Learning How to Learn
- Michigan Programming for Everybody
- JHU R Programming
- Google CBRS CPI Training

- Natural Language Processing (NLP)
- AI for Medicine
- Good with Words: Writing & Editing
- Infections Disease Modeling
- The Pronounciation of American English
- Software Testing Automation
- 深度學習
- 零基礎 Python 入門
- 數據科學
- 商務基礎
- Excel 辦公技能
- Data Science with Python
- Finance for Everyone
- Communication Skills for Engineers
- Sales Training
- 職業品牌管理職業生涯品牌管理
- Wharton Business Analytics
- Penn Positive Psychology
- Washington Machine Learning
- CalArts Graphic Design

- 專業證書
- MasterTrack 證書
- Google IT 支持
- IBM 數據科學
- Google Cloud Data Engineering
- IBM Applied AI
- Google Cloud Architecture
- IBM Cybersecurity Analyst
- Google IT Automation with Python
- IBM z/OS Mainframe Practitioner
- UCI Applied Project Management
- Instructional Design Certificate
- Construction Engineering and Management Certificate
- Big Data Certificate
- Machine Learning for Analytics Certificate
- Innovation Management & Entrepreneurship Certificate
- Sustainabaility and Development Certificate
- Social Work Certificate
- AI and Machine Learning Certificate
- Spatial Data Analysis and Visualization Certificate

- Computer Science Degrees
- Business Degrees
- 公共衛生學位
- Data Science Degrees
- 學士學位
- 計算機科學學士
- MS Electrical Engineering
- Bachelor Completion Degree
- MS Management
- MS Computer Science
- MPH
- Accounting Master's Degree
- MCIT
- MBA Online
- 數據科學應用碩士
- Global MBA
- Master's of Innovation & Entrepreneurship
- MCS Data Science
- Master's in Computer Science
- 公共健康碩士