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# Inferential Statistics

• Provider Coursera
• Subject Statistics & Probability
• Cost Free Online Course (Audit)
• Session In progress
• Language English
• Certificate Paid Certificate Available
• Effort 4-8 hours a week
• Start Date
• Duration 7 weeks long

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## Overview

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).

#### Taught by

Emiel van Loon and Annemarie Zand Scholten

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## Reviews for Coursera's Inferential Statistics 3.3 Based on 4 reviews

• 5 star 25%
• 4 star 25%
• 3 star 25%
• 2 star 0%
• 1 star 25%

Did you take this course? Share your experience with other students.

• 1
Ericdo1810 E
5.0 3 years ago
by completed this course, spending 4 hours a week on it and found the course difficulty to be hard.
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. This is a huge plus. Without challenge, good statistics understanding won't come.

It was a real challenge getting 100% for everything. For ev…
1 person found
Brandt P
3.0 3 years ago
by is taking this course right now, spending 3 hours a week on it and found the course difficulty to be very easy.
dropped dropped dropped dropped dropped dropped dropped dropped dropped dropped dropped dropped dropped dropped dropped dropped dropped dropped dropped dropped
0 person found
Rachael W
1.0 2 years ago
completed this course.
You must pay to access certain content of the course. This trend in Coursera is really a pity, and I am actively looking for other platforms for high quality MOOCs
Beniamino M
4.0 3 years ago
completed this course.
0 person found