Saltar al contenido principal

# 13.1: Error de muestreo (Sección @ref {samplingerror})

$$\newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} }$$

$$\newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}}$$

$$\newcommand{\id}{\mathrm{id}}$$ $$\newcommand{\Span}{\mathrm{span}}$$

( \newcommand{\kernel}{\mathrm{null}\,}\) $$\newcommand{\range}{\mathrm{range}\,}$$

$$\newcommand{\RealPart}{\mathrm{Re}}$$ $$\newcommand{\ImaginaryPart}{\mathrm{Im}}$$

$$\newcommand{\Argument}{\mathrm{Arg}}$$ $$\newcommand{\norm}[1]{\| #1 \|}$$

$$\newcommand{\inner}[2]{\langle #1, #2 \rangle}$$

$$\newcommand{\Span}{\mathrm{span}}$$

$$\newcommand{\id}{\mathrm{id}}$$

$$\newcommand{\Span}{\mathrm{span}}$$

$$\newcommand{\kernel}{\mathrm{null}\,}$$

$$\newcommand{\range}{\mathrm{range}\,}$$

$$\newcommand{\RealPart}{\mathrm{Re}}$$

$$\newcommand{\ImaginaryPart}{\mathrm{Im}}$$

$$\newcommand{\Argument}{\mathrm{Arg}}$$

$$\newcommand{\norm}[1]{\| #1 \|}$$

$$\newcommand{\inner}[2]{\langle #1, #2 \rangle}$$

$$\newcommand{\Span}{\mathrm{span}}$$ $$\newcommand{\AA}{\unicode[.8,0]{x212B}}$$

$$\newcommand{\vectorA}[1]{\vec{#1}} % arrow$$

$$\newcommand{\vectorAt}[1]{\vec{\text{#1}}} % arrow$$

$$\newcommand{\vectorB}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} }$$

$$\newcommand{\vectorC}[1]{\textbf{#1}}$$

$$\newcommand{\vectorD}[1]{\overrightarrow{#1}}$$

$$\newcommand{\vectorDt}[1]{\overrightarrow{\text{#1}}}$$

$$\newcommand{\vectE}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash{\mathbf {#1}}}}$$

$$\newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} }$$

$$\newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}}$$

Aquí vamos a muestrear repetidamente de la variable Altura NHANES para obtener la distribución muestral de la media.

sampSize <- 50 # size of sample
nsamps <- 5000 # number of samples we will take

# set up variable to store all of the results
sampMeans <- tibble(meanHeight=rep(NA,nsamps))

# Loop through and repeatedly sample and compute the mean
for (i in 1:nsamps) {
sampMeans$meanHeight[i] <- NHANES_adult %>% sample_n(sampSize) %>% summarize(meanHeight=mean(Height)) %>% pull(meanHeight) } Ahora vamos a trazar la distribución de muestreo. También se sobrepondremos la distribución muestral de la media predicha sobre la base de la media poblacional y la desviación estándar, para mostrar que describe adecuadamente la distribución muestral real. # pipe the sampMeans data frame into ggplot sampMeans %>% ggplot(aes(meanHeight)) + # create histogram using density rather than count geom_histogram( aes(y = ..density..), bins = 50, col = "gray", fill = "gray" ) + # add a vertical line for the population mean geom_vline(xintercept = mean(NHANES_adult$Height),
size=1.5) +
# add a label for the line
annotate(
"text",
x = 169.6,
y = .4,
label = "Population mean",
size=6
) +
# label the x axis
labs(x = "Height (inches)") +
# add normal based on population mean/sd
stat_function(
fun = dnorm, n = sampSize,
args = list(
mean = mean(NHANES_adult$Height), sd = sd(NHANES_adult$Height)/sqrt(sampSize)
),
size = 1.5,
color = "black",
linetype='dotted'
) 

This page titled 13.1: Error de muestreo (Sección @ref {samplingerror}) is shared under a not declared license and was authored, remixed, and/or curated by Russell A. Poldrack via source content that was edited to the style and standards of the LibreTexts platform; a detailed edit history is available upon request.