The Adventurer’s Notebook

Basic computer literacy

In the tutorial last week you’ve been playing around with R, RStudio and R scripts.

Stefano Coretta

Data types and reading data in R

Learn about types of data and how to import data in R

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Statistical variables

Learn about the type of statistical variables

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Statistical summaries

Learn about descriptive summary measures

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Research Methods and Hodotics

Research Methods are about the theory, methods and practice of conducting research

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Introduction to regression models (Part I)

Learn the basics of regression models, a powerful and flexible, yet simple, way of modelling data

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R basics

Learn the basics of R, a statistical programming language.

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R Troubleshooting

Learn about common R mistakes and where to find help

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Regression: Indexing of categorical predictors

Learn about indexing of categorical predictors in regression models

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Introduction to Quarto

Learn how to write dynamic documents with both text and code using Quarto

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R packages

Learn how to add functionality to R with packages

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Plotting basics

Learn the basics of plotting in R with ggplot2

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Reading multiple data files

An important skill to learn is how to read multiple files at once and save the output into a single tibble/data frame.

Wrangling data with R

Learn the basics of wrangling data with R

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Pivoting

Learn how to change the format of data tables from long to wide and viceversa using the pivot functions from tidyr

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Mutate data

Learn about mutating data using the tidyverse

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Bar charts

Bar charts are useful when you are counting things. For example:

Filter data

Data transformation is a fundamental aspect of data analysis.

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Introduction to regression models (Part II): include numeric predictors

Learn how to include numeric predictors in your regression models

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Introduction to regression models (Part III): include categorical predictors

Learn how to include categorical predictors in your regression models

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Regression models: working with MCMC draws

Learn how extract, wrangle and plot MCMC posterior draws

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Regression models: interactions

Add and interpret interactions in regression models

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Regression models: interactions between categorical predictors

Add and interpret interactions of two categorical predictors

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Regression: binary outcome variables

Learn how to fit regression models with binary outcome variable using the Bernoulli/binomial distribution

Stefano Coretta, Elizabeth Pankratz

Poisson regression: count

Learn how to fit Poisson regressions for count data

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Introduction to plotting

Learn about basic principles of good graphs

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Faceting plots

Sometimes we might want to separate the data into separate panels within the same plot.

Density plots

Density plots show the distribution (i.e. the probability density) of the values of a continuous variable.

Advanced plotting

In this tutorial, you can go through the different sections in any order you like and you can pick and choose which sections you want to work on. Note that you should…

Quantitative data analysis

Learn more about quantitative data analysis

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Inference and uncertainty

Learn about the inference process and the uncertainty that comes with it

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Empirical research and research context

Learn more about empirical research and the research context

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Research questions and hypotheses

Learn more about research questions, hypotheses and how to formulate them

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What is statistics?

Learn about the inference process and the uncertainty that comes with it

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File management

A Data Management Plan (DMP) covers anything related to data types, their volume (size), how you will acquire or collect them, where and how you will store them, and aspects…

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Research project management

Managing a research project, whether it’s a solo project like a dissertation or it’s a large-scale project with many people, involves a lot of project management skills.

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Reproducibility and replicability

Learn about the meaning of reproducible, replicable, robust and generalisable research

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Machine Learning

An introduction to Machine Learning and where to learn abou it

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R scripts

Learn about how to organise your code in R scripts

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Two statistical approaches to inference: Frequentist and Bayesian statistics

A conceptual introduction to the frequentist and Bayesian approaches to statistical inference

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Frequentist statistics and p-values

Learn about p-values and how to avoid common interpretation pitfalls

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Ordinal regression: modelling rating/Likert scales

Learn how to fit ordinal regressions for rating data

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Regression models: interactions between numeric predictors

Add and interpret interactions of two numeric predictors

Elizabeth Pankratz, Stefano Coretta

Catalogues and tips for R plots

The book Fundamentals of Data Visualisation by Wilke is a good introduction to data visualisation principles. You can find the book online here: Fundamentals of Data…

Interactive plotting with Plotly

Plotly is an Open Source graphing system, with interfaces to major languages like Python and R.

Bayesian regression in linguistic research

A selection of papers in linguistics that use Bayesian methods with a focus on regression models as of 2024

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Reporting your data analusis

Learn how to report summary measures, plot descriptions and regression models

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Regression models: a cheat-sheet

Learn about indexing of categorical predictors in regression models

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Sample size matters

Learn about sample size, why it is important and how to decide which sample size you should aim for.

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When frequentist null-ritualistic and Bayesian regression give you opposite results

Learn of the dangers of the null ritual in the context of regression models

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