From 7f7fbcc9e74dde62c454dcd46d48aa8e014f8211 Mon Sep 17 00:00:00 2001 From: Cooper Morris Date: Sun, 28 Aug 2016 08:05:27 -0500 Subject: [PATCH] Fixed three typos (#332) * Fixed Model Chapter Typo * Update rmarkdown.Rmd * Update model-basics.Rmd --- model-basics.Rmd | 2 +- model.Rmd | 2 +- rmarkdown.Rmd | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/model-basics.Rmd b/model-basics.Rmd index dc74286..ef4a8ca 100644 --- a/model-basics.Rmd +++ b/model-basics.Rmd @@ -237,7 +237,7 @@ These are exactly the same values we got with `optim()`! Behind the scenes `lm() ## Visualising models -For simple models, like the one above, you can figure out what pattern the model captures by carefully studying the model family and the fitted coefficients. And if you ever take a statistics course on modelling, you're likely to spend a lot of time doing just that. Here, however, we're going to take a different tack. We're going to focus on understanding a model by looking at its predictions. This has a big advantage: every type of predictive model makes predictions (otherwise what use would it be?) so we can use the same set of techniques to understand any type of predictive model. +For simple models, like the one above, you can figure out what pattern the model captures by carefully studying the model family and the fitted coefficients. And if you ever take a statistics course on modelling, you're likely to spend a lot of time doing just that. Here, however, we're going to take a different track. We're going to focus on understanding a model by looking at its predictions. This has a big advantage: every type of predictive model makes predictions (otherwise what use would it be?) so we can use the same set of techniques to understand any type of predictive model. It's also useful to see what the model doesn't capture, the so called residuals which are left after subtracting the predictions from the data. Residuals are powerful because they allow us to use models to remove striking patterns so we can study the subtler trends that remain. diff --git a/model.Rmd b/model.Rmd index b9e762c..df98e1a 100644 --- a/model.Rmd +++ b/model.Rmd @@ -20,7 +20,7 @@ This book is not going to give you a deep understanding of the mathematical theo * In [model building], you'll learn how to use models to pull out known patterns in real data. Once you have recognised an important pattern it's useful to make it explicitly in a model, because then you can - more easily see the subtler signals that remina. + more easily see the subtler signals that remain. * In [many models], you'll learn how to use many simple models to help understand complex datasets. This is a powerful technique, but to access diff --git a/rmarkdown.Rmd b/rmarkdown.Rmd index 806d416..5a28e1f 100644 --- a/rmarkdown.Rmd +++ b/rmarkdown.Rmd @@ -128,7 +128,7 @@ The following sections dives into the three components of an R Markdown document ## Text formatting with Markdown -Prose in `.Rmd` files is written in Markdown, a light weight set of conventions for formatting plan text files. Markdown is designed to be easy to read and easy to write. It is also very easy to learn. The guide below shows how to use Pandoc's Markdown, a slightly extended version of Markdown that R Markdown understands. +Prose in `.Rmd` files is written in Markdown, a light weight set of conventions for formatting plain text files. Markdown is designed to be easy to read and easy to write. It is also very easy to learn. The guide below shows how to use Pandoc's Markdown, a slightly extended version of Markdown that R Markdown understands. ```{r, echo = FALSE, comment = ""} cat(readr::read_file("rmarkdown/markdown.Rmd"))