week 12

Analysis 1 The sample average does differ significantly from the university’s estimate of a 70 degree average temp. the actual mean is 62.73.

```{r} mydata <- read.csv(“https://raw.githubusercontent.com/drkblake/Data/main/DormTemps.csv”)

if (!require(“tidyverse”)) install.packages(“tidyverse”) library(tidyverse)

mydata\(V1 <- mydata\)RoomTemp test_value = 70

ggplot(mydata, aes(x = V1)) + geom_histogram(color = “black”, fill = “#1f78b4”) + geom_vline(aes(xintercept = mean(V1)))

mydata %>% select(V1) %>% summarise( count = n(), mean = mean(V1, na.rm = TRUE), sd = sd(V1, na.rm = TRUE), min = min(V1, na.rm = TRUE), max = max(V1, na.rm = TRUE), W Statistic = shapiro.test(V1)\(statistic, `p-value` = shapiro.test(V1)\)p.value)

t.test(mydata$V1, mu = test_value)

Analysis 2

14.8% are in range, 85% are out of range. significant difference between the university's claim.

```{r}
if (!require("gmodels"))
  install.packages("gmodels")
if (!require("tidyverse"))
  install.packages("tidyverse")
library(tidyverse)
library(gmodels)
library(tidyverse)

mydata$V1 <- mydata$Range

ggplot(mydata, aes(x = V1)) +
  geom_bar(fill = "royalblue")

CrossTable(
  mydata$V1,
  prop.chisq = FALSE,
  prop.t = FALSE,
  prop.r = FALSE)

test <- chisq.test(table(mydata$V1))
test