Basic Quantitative Toolkit
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Regression: Crash Course Statistic
Learn how to build a regression model using an intuitive example.
Relational data
An example-driven resource that explains the concept of relational data in R.
Samples and Populations
Learn how a sample relates to a population, and various types of samples available to you as a researcher.
Six ways to share your research findings
Knowledge translation is an important final step of your research process; this guide offers guidance on how to be an effective research communicator.
Spurious Correlations: correlation is not causation
A clear illustration of an important point: even when two variables change in the same way, this tells you nothing about the relationship between them.
Stata for Students: Descriptive Statistics
Unsure how best to characterise your data in Stata? This resource is a definitive guide on several descriptive analyses relevant to social science research.
Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations
Even well-meaning scientists and students can fall prey to misrepresentations of statistical tests; this paper provides guidelines for avoiding common pitfalls.
Stats and R- Descriptive statistics in R
Descriptive statistics can summarise the properties of your data and show you what types of analyses would work best; this is crucial to know before conduct[ing] a full analysis.
Swirl- Learn R, in R.
The swirl package in R features short, self-paced and interactive tutorials that make learning R an active process.
The Binomial Distribution
When an event has two outcomes, its outcomes follow a binomial distribution; this resource explains important formulae related to the binomial distribution.
The central limit theorem | explained with a simple example
This video explains a fundamental concept in statistics; the sampling distribution of the mean will always be normally distributed.
The Correlation Coefficient (r)
Are you unsure how to interpret correlation coefficients or what kinds of data are suitable for these calculations? This resource introduces coefficients and how to calculate one in R.
The idea of significance tests
How likely is it that an outcome has happened by chance? Significance testing gets at this idea and this tutorial explains this using an intuitive example.
The Normal Distribution: Crash Course Statistics #19
This video introduces important terminology around normal distributions and how we can use them to compare parameters like the mean.
To Explain or to Predict
This article provides a thoughtful discussion of the difference between explanatory and predictive modelling, clarifying the distinct implications of each.
UCLA Advanced Research Computing, Statistical Methods and Data Analysis: Stata Learning Modules
Learn how to manage and organise your data using Stata, or review familiar concepts using focused articles.
Validity
This chapter explains why validity is an important factor to consider when measuring constructs in social science.
Virtual Math Lab- College Algebra
This resource meets you where you're at in your algebra journey, going over prerequisites such as scientific notation before walking through focused algebra modules.
Visualizations that Really Work
The most powerful data visualisations have a clear message—this guide provides thought-provoking questions and frameworks to help you decide what your message will be.
Welcome to the Tidyverse
Learn how to install the tidyverse package and how to use it.
