Example of a markdown file with figures and output ======================= ### David Hyrenbach ### `r as.character(Sys.Date())` ```{r echo=FALSE} # include this code chunk as-is to set options knitr::opts_chunk$set(comment=NA, prompt=TRUE, out.width=750, fig.height=8, fig.width=8) library(Rcmdr) library(car) library(RcmdrMisc) ``` ```{r echo=FALSE} # include this code chunk as-is to enable 3D graphs library(rgl) knitr::knit_hooks$set(webgl = hook_webgl) ``` ```{r} qnorm(c(3), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} qnorm(c(0.5), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} local({ .x <- seq(-3.291, 3.291, length.out = 1000) plotDistr(.x, pnorm(.x, mean = 0, sd = 1), cdf = TRUE, xlab = "x", ylab = "Cumulative Probability", main = paste("Normal Distribution: Mean=0, Standard deviation=1")) }) ``` ```{r} local({ .x <- seq(-3.291, 3.291, length.out = 1000) plotDistr(.x, dnorm(.x, mean = 0, sd = 1), cdf = FALSE, xlab = "x", ylab = "Density", main = paste("Normal Distribution: Mean=0, Standard deviation=1")) }) ``` ```{r} local({ .x <- seq(-3.291, 3.291, length.out = 1000) plotDistr(.x, dnorm(.x, mean = 0, sd = 1), cdf = FALSE, xlab = "x", ylab = "Density", main = paste("Normal Distribution: Mean=0, Standard deviation=1"), regions = list(c(-1, 1)), col = c("#C0C0C0", "#BEBEBE"), legend.pos = "topright") }) ``` ```{r} local({ .x <- seq(-3.291, 3.291, length.out = 1000) plotDistr(.x, dnorm(.x, mean = 0, sd = 1), cdf = FALSE, xlab = "x", ylab = "Density", main = paste("Normal Distribution: Mean=0, Standard deviation=1"), regions = list(c(-0.674489750196082, 0.674489750196082)), col = c("#C0C0C0", "#BEBEBE"), legend.pos = "topright") }) ``` ```{r} pnorm(c(3), mean = 0, sd = 1, lower.tail = TRUE) ``` ```{r} qnorm(c(0.5), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} qnorm(c(0.5), mean = 0, sd = 1, lower.tail = TRUE) ``` ```{r} qnorm(c(0.5), mean = 0, sd = 1, lower.tail = TRUE) ``` ```{r} qnorm(c(-0.5), mean = 0, sd = 1, lower.tail = TRUE) ``` ```{r} qnorm(c(-0.5), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} qnorm(c(0.5), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} qnorm(c(0.5), mean = 0, sd = 1, lower.tail = TRUE) ``` ```{r} qnorm(c(0.5), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} qnorm(c(-0.5), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} qnorm(c(0.33), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} qnorm(c(0.5), mean = 0, sd = 1, lower.tail = TRUE) ``` ```{r} qnorm(c(0.5), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} qnorm(c(0.5), mean = 0, sd = 1, lower.tail = TRUE) ``` ```{r} qnorm(c(0.5), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} pnorm(c(0.5), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} pnorm(c(0), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} pnorm(c(0), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} pnorm(c(1), mean = 0, sd = 1, lower.tail = TRUE) ``` ```{r} pnorm(c(1), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} qnorm(c(0.5), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} qnorm(c(0.5), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} qnorm(c(0.5), mean = 0, sd = 1, lower.tail = TRUE) ``` ```{r} qnorm(c(0.85), mean = 0, sd = 1, lower.tail = TRUE) ``` ```{r} qnorm(c(0.99), mean = 0, sd = 1, lower.tail = TRUE) ``` ```{r} qnorm(c(0.99), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} qnorm(c(0), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} qnorm(c(0), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} qnorm(c(0), mean = 0, sd = 1, lower.tail = TRUE) ``` ```{r} qnorm(c(0.5), mean = 0, sd = 1, lower.tail = TRUE) ``` ```{r} qnorm(c(0.5), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} qnorm(c(0.5), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} pnorm(c(0), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} pnorm(c(0), mean = 0, sd = 1, lower.tail = TRUE) ``` ```{r} pnorm(c(3), mean = 0, sd = 1, lower.tail = TRUE) ``` ```{r} pnorm(c(3), mean = 0, sd = 1, lower.tail = FALSE) ``` ```{r} local({ .x <- seq(-3.291, 3.291, length.out = 1000) plotDistr(.x, dnorm(.x, mean = 0, sd = 1), cdf = FALSE, xlab = "x", ylab = "Density", main = paste("Normal Distribution: Mean=0, Standard deviation=1"), regions = list(c(0, 1), c(1, 2)), col = c("#C0C0C0", "#BEBEBE"), legend.pos = "topright") }) ``` ```{r} local({ .x <- seq(-3.291, 3.291, length.out = 1000) plotDistr(.x, dnorm(.x, mean = 0, sd = 1), cdf = FALSE, xlab = "x", ylab = "Density", main = paste("Normal Distribution: Mean=0, Standard deviation=1"), regions = list(c(0, 1), c(1, 2)), col = c("#FF0000", "#0080FF"), legend.pos = "topright") }) ``` ```{r} local({ .x <- seq(-3.291, 3.291, length.out = 1000) plotDistr(.x, pnorm(.x, mean = 0, sd = 1), cdf = TRUE, xlab = "x", ylab = "Cumulative Probability", main = paste("Normal Distribution: Mean=0, Standard deviation=1")) }) ``` ```{r} local({ .x <- seq(-3.291, 3.291, length.out = 1000) plotDistr(.x, pnorm(.x, mean = 0, sd = 1), cdf = TRUE, xlab = "x", ylab = "Cumulative Probability", main = paste("Normal Distribution: Mean=0, Standard deviation=1")) }) ``` ```{r} NormalSamples <- as.data.frame(matrix(rnorm(10 * 100, mean = 0, sd = 1), ncol = 100)) rownames(NormalSamples) <- paste("sample", 1:10, sep = "") colnames(NormalSamples) <- paste("obs", 1:100, sep = "") NormalSamples <- within(NormalSamples, { mean <- rowMeans(NormalSamples[, 1:100]) sd <- apply(NormalSamples[, 1:100], 1, sd) }) ``` ```{r} NormalSamples <- as.data.frame(matrix(rnorm(1 * 100, mean = 0, sd = 1), ncol = 100)) rownames(NormalSamples) <- "sample" colnames(NormalSamples) <- paste("obs", 1:100, sep = "") ``` ```{r} local({ .x <- seq(0.001, 7.601, length.out = 1000) plotDistr(.x, dexp(.x, rate = 1), cdf = FALSE, xlab = "x", ylab = "Density", main = paste("Exponential Distribution: Rate=1")) }) ```