first draft of resampling finished. need to test it

Statistical_Inference/MANIFEST

@@ -10,5 +10,5 @@ T_Confidence_Intervals
 Hypothesis_Testing
 P_Values
 Power
+Multiple_Testing
 Resampling
-

Statistical_Inference/Power/lesson

@@ -401,7 +401,7 @@
   Hint: Since you're doubling the denominator (sd) you have to double the numerator (delta) in order to keep the effect size constant.
 
 - Class: text
-  Output: Now for a quick review - we call this the power.u.test LOL
+  Output: Now for a quick review. We call this the power.u.test since it comes after the power.t.test. LOL. 
 
 - Class: mult_question
   Output: 1. The level of a test is specified by what?

Statistical_Inference/Resampling/fatherson.R

@@ -1,4 +1,5 @@
 x <- fs$sheight
+y <- fs$fheight
 n <- length(x)
 B <- 10000
 resamples <- matrix(sample(x,
@@ -11,3 +12,4 @@ g = g + geom_density(size = 2, fill = "red")
 #g = g + geom_histogram(alpha = .20, binwidth=.3, colour = "black", fill = "blue", aes(y = ..density..)) 
 g = g + geom_vline(xintercept = median(x), size = 2)
 print(g)
+

Statistical_Inference/Resampling/initLesson.R

@@ -2,3 +2,4 @@
 library(ggplot2)
 fname <- paste(getwd(),"Statistical_Inference/Hypothesis_Testing/father_son.csv",sep="/")
 fs <- read.csv(fname)
+data(InsectSprays)

Statistical_Inference/Resampling/insectHisto.R

@@ -0,0 +1,5 @@
+g = ggplot(data.frame(perms = perms),
+           aes(permutations))
+g = g + geom_histogram(fill = "lightblue", color = "black", binwidth = 1)
+g = g + geom_vline(xintercept = obs, size = 2)
+print(g)

Statistical_Inference/Resampling/insectSprays.R

@@ -0,0 +1,12 @@
+g = ggplot(InsectSprays, aes(spray, count, fill = spray))
+g = g + geom_boxplot()
+print(g)
+subdata <- InsectSprays[InsectSprays$spray %in% c("B", "C"),]
+Bdata <- subdata[subdata$spray=="B",]
+Cdata <- subdata[subdata$spray=="C",]
+group <- as.character(subdata$spray)
+testStat <- function(w, g) mean(w[g == "B"]) - mean(w[g == "C"])
+BCcounts <- subdata$count
+obs <- testStat(BCcounts, group)
+
+

Statistical_Inference/Resampling/insectSprays2.R

@@ -0,0 +1,12 @@
+g = ggplot(InsectSprays, aes(spray, count, fill = spray))
+g = g + geom_boxplot()
+print(g)
+subdata <- InsectSprays[InsectSprays$spray %in% c("D", "E"),]
+Ddata <- subdata[subdata$spray=="D",]
+Edata <- subdata[subdata$spray=="E",]
+group <- as.character(subdata$spray)
+testStat <- function(w, g) mean(w[g == "D"]) - mean(w[g == "E"])
+DEcounts <- subdata$count
+obs <- testStat(DEcounts, group)
+
+

Statistical_Inference/Resampling/plot1.R

@@ -2,9 +2,10 @@ nosim <- 1000
 cfunc <- function(x, n) mean(x)
 g1 = ggplot(data.frame(y = rep(1/6, 6), x = 1 : 6), aes(y = y, x = x))
 g1 = g1 + geom_bar(stat = "identity", fill = "lightblue", colour = "black")
-
+#print(g1)
 dat <- data.frame(x = apply(matrix(sample(1 : 6, nosim * 50, replace = TRUE), 
                                    nosim), 1, mean))
 g2 <- ggplot(dat, aes(x = x)) + geom_histogram(binwidth=.2, colour = "black", fill = "salmon", aes(y = ..density..)) 
 print(g2)
 #grid.arrange(g1, g2, ncol = 2)
+

Statistical_Inference/Resampling/plot2.R

@@ -11,4 +11,5 @@ resampledMeans = apply(resamples, 1, mean)
 g1 <- ggplot(as.data.frame(prop.table(table(x))), aes(x = x, y = Freq)) + geom_bar(colour = "black", fill = "lightblue", stat = "identity") 
 g2 <- ggplot(data.frame(x = resampledMeans), aes(x = x)) + geom_histogram(binwidth=.2, colour = "black", fill = "salmon", aes(y = ..density..)) 
 #grid.arrange(g1, g2, ncol = 2)
-print(g1)
+print(g1)
+