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x_1 denotes a variable, while a_1 denotes a parameter (#920)

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Mitsuo Shiota 2021-02-09 02:35:02 +09:00 committed by GitHub
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model-basics.Rmd
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@ -350,7 +350,7 @@ The following sections expand on how this formula notation works for categorical
### Categorical variables
Generating a function from a formula is straight forward when the predictor is continuous, but things get a bit more complicated when the predictor is categorical. Imagine you have a formula like `y ~ sex`, where sex could either be male or female. It doesn't make sense to convert that to a formula like `y = x_0 + x_1 * sex` because `sex` isn't a number - you can't multiply it! Instead what R does is convert it to `y = x_0 + x_1 * sex_male` where `sex_male` is one if `sex` is male and zero otherwise:
Generating a function from a formula is straight forward when the predictor is continuous, but things get a bit more complicated when the predictor is categorical. Imagine you have a formula like `y ~ sex`, where sex could either be male or female. It doesn't make sense to convert that to a formula like `y = a_0 + a_1 * sex` because `sex` isn't a number - you can't multiply it! Instead what R does is convert it to `y = a_0 + a_1 * sex_male` where `sex_male` is one if `sex` is male and zero otherwise:
```{r}
df <- tribble(