Data and Software for "Lessons in Statistical Thinking"
Convenience function for adding labels to point_plot or others without...
Draw a DAG
Helpers for specifying nodes in simulations
Construct and modify data simulations
Run a datasim simulation, producing a data frame
Data from McClave-Sincich Statistics 11/e
Evaluate a model on inputs
Helper functions to evaluate models
Check model type against model specification and data
Graph a model function
Convert a model to a skeleton
train a model, easily
Construct a model and return the model values
Cull objects used with do()
Create vector based on roughly equally sized groups
One-step data graphics
Nice printing of some internal objects
A printing method for model objects
Sample from a college registrar's database
Summaries of regression models
Samples from various kinds of objects
Short, simple data frames for textbook examples
Simulations for use in Lessons in Statistical Thinking
Evaluate a tilde expression on a data frame
Add a slope "rose" to a plot.
Run the left side of the pipeline multiple times.
Utilities
Zero-one transformation for categorical variable
"Lessons in Statistical Thinking" D.T. Kaplan (2014) <https://dtkaplan.github.io/Lessons-in-statistical-thinking/> is a textbook for a first or second course in statistics that embraces data wrangling, causal reasoning, modeling, statistical adjustment, and simulation. 'LSTbook' supports the student-centered, tidy, pipeline-oriented computing style featured in the book.