Ensure every chapter has a heading

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hadley 2016-02-11 16:31:34 -06:00
parent 27cc6617bb
commit d69eeff57e
8 changed files with 17 additions and 2 deletions

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title: Communicate your work title: Communicate your work
--- ---
# Communicate your work
Reproducible, literate code is the data science equivalent of the Scientific Report (i.e, Intro, Methods and materials, Results, Discussion). Reproducible, literate code is the data science equivalent of the Scientific Report (i.e, Intro, Methods and materials, Results, Discussion).

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title: Databases title: Databases
--- ---
# Databases
### Two-table verbs ### Two-table verbs
Each two-table verb has a straightforward SQL equivalent: Each two-table verb has a straightforward SQL equivalent:

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title: Model title: Model
--- ---
# Model
A model is a function that summarizes how the values of one variable vary in response to the values of other variables. Models play a large role in hypothesis testing and prediction, but for the moment you should think of models just like you think of statistics. A statistic summarizes a *distribution* in a way that is easy to understand; and a model summarizes *covariation* in a way that is easy to understand. In other words, a model is just another way to describe data. A model is a function that summarizes how the values of one variable vary in response to the values of other variables. Models play a large role in hypothesis testing and prediction, but for the moment you should think of models just like you think of statistics. A statistic summarizes a *distribution* in a way that is easy to understand; and a model summarizes *covariation* in a way that is easy to understand. In other words, a model is just another way to describe data.
This chapter will explain how to build useful models with R. This chapter will explain how to build useful models with R.
@ -298,6 +300,7 @@ ns() # natural splines
``` ```
```{r} ```{r}
library(splines)
tidy(lm(income ~ ns(education, knots = c(10, 17)), data = heights)) tidy(lm(income ~ ns(education, knots = c(10, 17)), data = heights))
tidy(lm(income ~ ns(education, df = 4), data = heights)) tidy(lm(income ~ ns(education, df = 4), data = heights))
``` ```
@ -314,7 +317,7 @@ ggplot(data = heights, mapping = aes(x= education, y = income)) +
```{r} ```{r}
gam(income ~ s(education), data = heights) gam(income ~ s(education), data = heights)
ggplot(data = heights, mapping = aes(x= education, y = income)) + ggplot(data = heights, mapping = aes(x = education, y = income)) +
geom_point() + geom_point() +
geom_smooth(method = gam, formula = y ~ s(x)) geom_smooth(method = gam, formula = y ~ s(x))
``` ```

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title: Save time by programming title: Save time by programming
--- ---
# Programming
Computer-human communication matters. Computer-human communication matters.

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library(magrittr) library(magrittr)
``` ```
## Robust code # Robust code
(This is an advanced topic. You shouldn't worry too much about it when you first start writing functions. Instead you should focus on getting a function that works right for the easiest 80% of the problem. Then in time, you'll learn how to get to 99% with minimal extra effort. The defaults in this book should steer you in the right direction: we avoid teaching you functions with major suprises.) (This is an advanced topic. You shouldn't worry too much about it when you first start writing functions. Instead you should focus on getting a function that works right for the easiest 80% of the problem. Then in time, you'll learn how to get to 99% with minimal extra effort. The defaults in this book should steer you in the right direction: we avoid teaching you functions with major suprises.)

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title: Do science with data title: Do science with data
--- ---
# Do science with data
The scientific method guides data science. Data science solves known problems with the scientific method. The scientific method guides data science. Data science solves known problems with the scientific method.

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title: Understand your data title: Understand your data
--- ---
# Understand your data
Data poses a cognitive problem; Data comprehension is a skill. Data poses a cognitive problem; Data comprehension is a skill.

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title: Work with your data title: Work with your data
--- ---
# Work with your data
With data, the relationships between values matter as much as the values themselves. Tidy data encodes those relationships. With data, the relationships between values matter as much as the values themselves. Tidy data encodes those relationships.