Quick Reference

Index of Topics

If you’re looking for a particular section of a tutorial, use this handy summary to jump straight to the section you want.

Topic Sub-Topic
01: IntRoduction
Orientation R is for Reproducibility, Using the Tutorials, The RStudio Interface
Errors GlossoRlia: the Language of Errors
Types of Data Numeric Data, Character Data, Factor Data, Logical Data
Class and Coercion
Objects Creating an Object, Naming Objects, Calling an Object, Using Objects, Overwriting Objects
Quick Test: t-test
02: IntRoduction II
Setup Projects, Documents
Packages Loading tidyverse
Functions Basics and Help, Arguments, Using Functions, Passing Multiple Values to Arguments
Packages Revisited Installing Packages, Loading Packages
Exercises
03: Datasets
Setup
Reading In File Types, From File, From URL
Codebook
Viewing Call the Object, A Glimpse of the Data, View Mode
Overall Summaries Basic Summary, Other Summaries
The Pipe
Describing Datasets
Describing Variables Counting, Subsetting, Descriptives, Visualisations
Exercises
04: Filter and Select
Setup Packages, Data
Thinking Like a Coder
Filter General Format, Single Assertions, Multiple Assertions, Exercises, Data Cleaning
Select General Format, Selecting Directly, Using tidyselect, Using Functions
Exporting
Quick Test
05: Mutate
Setup Packages, Data
General Format
Adding New Variables
Changing Existing Variables
Composite Scores
Exercises
Conditionals One-Variable Input, Multi-Variable Input
Iteration Exercises
Quick Test: \(\chi^2\)
Exercises
06: Reproducible Linear Models
The Linear Model Data and Codebook, One Predictor, Hierarchical Models, Assumptions Checks, Robust Models
Exercises
Reproducible Analysis Same Results, Correct Analysis
Reproducible Reporting Creating a Quarto Document, Creating a Code Chunk, Body Text, Reporting, Rendering
07: Summarise
Setup Packages, Data
Summarising Overall, By Group, Multiple Variables
Exercises
Formatting Tables Quarto to HTML/PDF, Exporting
Quick Test: Correlation Visualisation, Testing Correlation
Exercises
08: Visualisations
NA Data Visualisation Resources, What do UGs know?
Setup Packages, Data
Grammar of Graphics Layers, Mapping, Geoms, etc.
Histograms and Density Plots Adjusting Binwidth, Colour and Fill Manual, Adjusting Axes with scale_*(), Adding a Theme, Splitting by Group
Barplots Position Dodge, Reordering Categories
Raincloud and Violin Plots Calculating Stats
Scatterplots Line of Best Fit, Colour and Fill Palette, 3D Plots
Reporting With Quarto, Exporting and Linking
09: Labelled Data and Qualtrics
NA Acknowledgements
Qualtrics SAV Data, Setting Up Qualtrics, Library, Exporting Data
Setup Packages, Data, Codebook
Variable Names Default Variable Names, Renaming
Exercises: Names
Labelled Data Working with Labels, Variable Labels, Value Labels, Missing Values
Exercises: Labels
Data Dictionaries
Converting Variables Factors, Numeric, Efficient Conversion
Exercise: Conversion and Wrangling
Well done!
10: Putting it all together
NA Reproducibility Certification
Setup Packages, Data
Reproducibility Report: Part One Section 1: Reproducibility of Data Processing, Section 2: Reproducibility of Analysis Environment, Section 3: Reproducibility of Analysis Pipeline
ANOVA Speedrun One-Way ANOVA, Factorial Designs, Mixed Designs
Reproducibility Report: Part Two
Exercises Option 1: Continue working, Option 2: Work on one of your own projects, Option 3: Conduct a reproducibility check on a published study
Submitting Your Work
Final Thoughts

Index of Functions

Looking for a function you can’t quite remember how to use? You’re in the right place! The table below is arranged alphabetically by function name, and the linked full name (including relevant package calls) will take you to the help documentation.

Function Name Link to Help Documentation Used In…
across() dplyr::across() 07: Summarise
10: Putting it all together
all() all() 04: Filter and Select
anova() anova() 06: Reproducible Linear Models
any() any() 04: Filter and Select
apa_print() papaja::apa_print() 06: Reproducible Linear Models
10: Putting it all together
apa_table() papaja::apa_table() 06: Reproducible Linear Models
10: Putting it all together
arrange() dplyr::arrange() 04: Filter and Select
as.character() as.character() 06: Reproducible Linear Models
as.factor() as.factor() 06: Reproducible Linear Models
as.numeric() as.numeric() 01: IntRoduction
as_tibble() tibble::as_tibble() 09: Labelled Data and Qualtrics
autoplot() ggplot2::autoplot() 06: Reproducible Linear Models
between() dplyr::between() 04: Filter and Select
boxplot() boxplot() 03: Datasets
c() c() 01: IntRoduction
02: IntRoduction II
03: Datasets
04: Filter and Select
05: Mutate
06: Reproducible Linear Models
07: Summarise
09: Labelled Data and Qualtrics
10: Putting it all together
c_across() dplyr::c_across() 05: Mutate
cat() cat() 06: Reproducible Linear Models
chisq.test() chisq.test() 05: Mutate
class() class() 01: IntRoduction
06: Reproducible Linear Models
contains() dplyr::contains() 04: Filter and Select
07: Summarise
09: Labelled Data and Qualtrics
contr.sum() contr.sum() 10: Putting it all together
contrasts() contrasts() 10: Putting it all together
cor.test() cor.test() 07: Summarise
correlation() correlation::correlation() 07: Summarise
count() dplyr::count() 03: Datasets
04: Filter and Select
05: Mutate
data() data() 06: Reproducible Linear Models
deframe() tibble::deframe() 07: Summarise
describe_distribution() datawizard::describe_distribution() 03: Datasets
detach() detach() 10: Putting it all together
drop_na() tidyr::drop_na() 04: Filter and Select
emmeans() emmeans::emmeans() 10: Putting it all together
everything() dplyr::everything() 04: Filter and Select
factor() factor() 01: IntRoduction
05: Mutate
10: Putting it all together
filter() dplyr::filter() 04: Filter and Select
05: Mutate
geom_histogram() ggplot2::geom_histogram() 08: Visualisations
ggpairs() GGally::ggpairs() 07: Summarise
ggscatmat() GGally::ggscatmat() 07: Summarise
glance() broom::glance() 06: Reproducible Linear Models
10: Putting it all together
glimpse() dplyr::glimpse() 03: Datasets
gsub() gsub() 07: Summarise
09: Labelled Data and Qualtrics
here() here::here() 04: Filter and Select
05: Mutate
06: Reproducible Linear Models
07: Summarise
08: Visualisations
09: Labelled Data and Qualtrics
10: Putting it all together
hist() hist() 03: Datasets
ifelse() ifelse() 08: Visualisations
install.packages() install.packages() 10: Putting it all together
installed.packages() installed.packages() 10: Putting it all together
invisible() invisible() 10: Putting it all together
is.character() is.character() 04: Filter and Select
is.na() is.na() 04: Filter and Select
09: Labelled Data and Qualtrics
is.null() is.null() 09: Labelled Data and Qualtrics
joint_tests() emmeans::joint_tests() 10: Putting it all together
kable_classic() kableExtra::kable_classic() 07: Summarise
kable_styling() kableExtra::kable_styling() 03: Datasets
04: Filter and Select
05: Mutate
07: Summarise
08: Visualisations
10: Putting it all together
lapply() lapply() 10: Putting it all together
levels() levels() 06: Reproducible Linear Models
library() library() 02: IntRoduction II
03: Datasets
04: Filter and Select
05: Mutate
06: Reproducible Linear Models
07: Summarise
08: Visualisations
09: Labelled Data and Qualtrics
10: Putting it all together
lm() lm() 06: Reproducible Linear Models
10: Putting it all together
lmRob() robust::lmRob() 06: Reproducible Linear Models
max() max() 04: Filter and Select
07: Summarise
mean() mean() 01: IntRoduction
02: IntRoduction II
03: Datasets
median() median() 02: IntRoduction II
03: Datasets
04: Filter and Select
min() min() 04: Filter and Select
model_parameters() parameters::model_parameters() 06: Reproducible Linear Models
10: Putting it all together
mutate() dplyr::mutate() 06: Reproducible Linear Models
na_values() labelled::na_values() 09: Labelled Data and Qualtrics
names() names() 03: Datasets
07: Summarise
09: Labelled Data and Qualtrics
10: Putting it all together
ncol() ncol() 03: Datasets
nrow() nrow() 03: Datasets
04: Filter and Select
options() options() 08: Visualisations
paste() paste() 10: Putting it all together
paste0() paste0() 09: Labelled Data and Qualtrics
10: Putting it all together
pick() dplyr::pick() 04: Filter and Select
plot() plot() 03: Datasets
position_jitterdodge() ggplot2::position_jitterdodge() 10: Putting it all together
print() print() 07: Summarise
pull() dplyr::pull() 03: Datasets
05: Mutate
07: Summarise
range() range() 02: IntRoduction II
03: Datasets
rd() weights::rd() 02: IntRoduction II
read_csv() readr::read_csv() 03: Datasets
04: Filter and Select
05: Mutate
06: Reproducible Linear Models
07: Summarise
08: Visualisations
10: Putting it all together
read_sav() haven::read_sav() 09: Labelled Data and Qualtrics
report() report::report() 04: Filter and Select
06: Reproducible Linear Models
07: Summarise
return() return() 07: Summarise
rglwidget() rgl::rglwidget() 08: Visualisations
rnorm() rnorm() 02: IntRoduction II
06: Reproducible Linear Models
round() round() 02: IntRoduction II
03: Datasets
06: Reproducible Linear Models
rowMeans() rowMeans() 05: Mutate
rowSums() rowSums() 04: Filter and Select
rowid_to_column() tibble::rowid_to_column() 10: Putting it all together
rownames() rownames() 10: Putting it all together
scroll_box() kableExtra::scroll_box() 09: Labelled Data and Qualtrics
sd() sd() 03: Datasets
07: Summarise
select() dplyr::select() 05: Mutate
sessionInfo() sessionInfo() 10: Putting it all together
set.seed() set.seed() 02: IntRoduction II
06: Reproducible Linear Models
08: Visualisations
setdiff() setdiff() 10: Putting it all together
sqrt() sqrt() 07: Summarise
starts_with() dplyr::starts_with() 04: Filter and Select
05: Mutate
09: Labelled Data and Qualtrics
str_to_sentence() stringr::str_to_sentence() 07: Summarise
str_to_title() stringr::str_to_title() 07: Summarise
08: Visualisations
10: Putting it all together
sub() sub() 10: Putting it all together
sum() sum() 04: Filter and Select
05: Mutate
summary() summary() 03: Datasets
06: Reproducible Linear Models
t.test() t.test() 01: IntRoduction
02: IntRoduction II
04: Filter and Select
theme_apa() papaja::theme_apa() 08: Visualisations
10: Putting it all together
theme_minimal() ggplot2::theme_minimal() 10: Putting it all together
tidy() broom::tidy() 06: Reproducible Linear Models
10: Putting it all together
to_factor() labelled::to_factor() 09: Labelled Data and Qualtrics
tolower() tolower() 07: Summarise
toupper() toupper() 07: Summarise
unclass() unclass() 09: Labelled Data and Qualtrics
ungroup() dplyr::ungroup() 05: Mutate
09: Labelled Data and Qualtrics
unlist() unlist() 09: Labelled Data and Qualtrics
user_na_to_na() labelled::user_na_to_na() 09: Labelled Data and Qualtrics
val_label() labelled::val_label() 09: Labelled Data and Qualtrics
val_labels() labelled::val_labels() 09: Labelled Data and Qualtrics
var_label() labelled::var_label() 09: Labelled Data and Qualtrics
where() dplyr::where() 04: Filter and Select
10: Putting it all together
which() which() 07: Summarise