Inferential Statistics

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. Normally you would also learn how to perform these tests using freely available software R. Due to technical issues we are not able to do so. We will try to offer this again soon. 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).

Status: Statistical Modeling

Status: Statistical Programming

Course15 hours

Featured reviews

5.0Reviewed Apr 14, 2016

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.

4.0Reviewed May 8, 2020

Wish there was a way to accept alternative methods on R assignments - got the answer but would not accept string of code

4.0Reviewed Jan 7, 2017

Not giving 5 stars only because it was fast paced. With a low grasping power i had to watch the video again and again. Otherwise the content in the video is to the point.

4.0Reviewed Apr 9, 2024

Mostly good, easy to understand. Would like to also understand how to work with actual, bigger data with R etc

5.0Reviewed Jul 3, 2017

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!

5.0Reviewed Oct 24, 2018

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

4.0Reviewed Jun 27, 2023

The quizzes and R lab were beneficial. The lectures were good. However, it left some questions unclear, and I, as a learner, wished for something more to be done.

4.0Reviewed Mar 28, 2016

A good introduction with very good videos and exercises. I'm only not giving 5 stars due to the relative lack of clarity in the final week and the lack of feedback on the final exam.

5.0Reviewed Feb 10, 2017

Excellent Course for Inferential Statistics. Really Enjoyed the course. R quiz give hands-on on the data sets.

5.0Reviewed Jul 24, 2020

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.

5.0Reviewed Sep 23, 2020

Excellent course and it was a good revision of what i have learnt long back. The assessment is also done very well

4.0Reviewed Nov 2, 2024

this is a pretty challenging course for those who are new in statistics.I feel confused about the videos sometimes,and I think more examples should be used to explain the formulas more clearly.