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Inferential Statistics

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41 hours
English
University of Amsterdam
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For Rs. 2182
Intermediate
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Checklist

Certification

You will get a certificate on completing this course.

University

The course is from one of the top universities of the world - University of Amsterdam.

Price

This course costs very less.

Difficulty

The students of this course have found this course difficult.

Content

The students of this course have liked the content of this course.

Assignments

The students of this course have not liked the assignments of this course.

Teaching

The students of this course have liked how the instructor has taught this course.

Satisfaction

The students of this course are overall satisfied with this course.

Edvicer's Rewards

You can get a cashback of ₹ 100 on buying this course.

Why should you choose this course?

Description

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).

Syllabus

Before we get started...
Comparing two groups
Categorical association
Simple regression
Multiple regression
Analysis of variance
Non-parametric tests
Exam time!

What others say about this course

Reviews from Coursera

An overview of inference, light on the math, light on the theory, and with an unfortunate failure to reinforce what may be the most important part of practice: what should be done when conditions for a  Read More ...

A very good introduction to the fundamentals of inference and NHST. It's very important that you do all excercises and readings or you will not learn as much. Also, the course won't provide a lot of in  Read More ...

The course did teach statistics but there were some problems with R commands, assignment expectations and grading outcomes. For one, this course really needs to do a better job of emphasizing that the   Read More ...

The teacher lacks the ability of mathematical description, including clearing defining concepts, describing everything in mathematical languages, and showing math formulas of t-tests. She hopes to hide  Read More ...

This course by Professor Çetinkaya-Rundel is awesome because it is taught in a very clear and vivid way. Lab section and forum are so dope that I love them so much! Definitely strong recommendation!!!

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