---
title: "Errata"
author: "Foundations and Applications of Statistics"
date: "Second Edition"
output:
knitr:::html_vignette:
variant: html+multiline_tables
fig_caption: no
toc: no
html_document:
toc: no
pdf_document:
highlight: null
number_sections: no
vignette: |
%\VignetteIndexEntry{Errata}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r setup, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
```
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Page Location Issue
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25 printed: `tally(death ~ victim, data = DeathPenalty)`
correct: `tally(death ~ defendant, data = DeathPenalty)`
Exercise 1.20 `geyser` is in the `MASS` package (see page 14).
Use `MASS::geyser` to access this data set.
285 last line printed: $-2n\pi$
correct: $-n\pi$
286 lines 9-10 printed: correct when $\pi_0 = 0$ but overestimates ... when $\pi_0 > 0$
correct: correct when $\pi_0 = 1/2$ but overestimates ... when $\pi_0 \neq 1/2$
331 The problem could be clarified to indicate that the *first* moment
is not useful. The second moment could be used.
373 printed: $W = -2 \log\left(\frac{L(\theta_0)}{L(\hat\theta)} \right) = 2 \left(\log(\hat \theta) - \log(\theta_0)\right) \approx I(\hat \theta) (\theta_0 - \hat\theta)^2$
correct: $W = -2 \log\left( \frac{L(\theta_0)}{L(\hat\theta)} \right) = 2 \left(l(\hat \theta) - l(\theta_0)\right) \approx I(\hat \theta) (\theta_0 - \hat\theta)^2$
380 lines 6, 11, 13 printed: `pnorm()`, `pchisq()`, `pchisq()`
correct: `qnorm()`, `qchisq()`, `qchisq()`.
388 printed: The assymptotic distribution of $\Lambda$
correct: The assymptotic distribution of $W = -2 \log(\Lambda)$
389 printed: `makLik`
correct: `maxLik`
446 Exercise 5.18 printed: log of the odds ratio
correct: log of the odds
447 line 1 printed: poison
correct: Poisson
498 line 5 printed: internally studentized residuls
correct: internally studentized residuals
747 Exercise A.11 Unfortunately, the `weatherData` package has been
removed from CRAN.
Similar data now live in `mosaicData::Weather`,
but the data for several cities are
already contained in a single data frame,
so there is no need to merge from multiple sources.
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