lecture-10.Rmd

---
title: "Lecture 10"
---


### Lecture handout:  
chp6-handout.pdf
chp7-handout.pdf

### Lecture slides (w/ answers):  
chp6.pdf
chp7.pdf

### Textbook: 
Chapter 6, Inference for Categorical Data, Chapter 7, Inference for Numerical Data

### R Topics:

#### X^2 distribution
```{r eval=FALSE}
x <- seq(0,20, by=.1)
df <- data.frame(x=x, y1=dchisq(x, 1), y2=dchisq(x,2), y3=dchisq(x,3))
ggplot(df) + geom_line(aes(x=x,y=y1), color="steelblue1") + geom_line(aes(x=x,y=y2), color="steelblue2") + geom_line(aes(x=x,y=y3), color="steelblue3") 
```

#### t-distribution
```{r eval=FALSE}
x<-seq(-4,4,by=.1)
df<-data.frame(x=x, ynorm=dnorm(x), yt1=dt(x,1), yt2=dt(x,2), yt3=dt(x,3))
ggplot(df) + geom_line(aes(x=x,y=ynorm)) + geom_line(aes(x=x,y=yt1)) + geom_line(aes(x=x,y=yt2)) + geom_line(aes(x=x,y=yt3))
ggplot(df) + geom_line(aes(x=x,y=ynorm), color="red") + geom_line(aes(x=x,y=yt1), color="grey80") + geom_line(aes(x=x,y=yt2), color="gray50") + geom_line(aes(x=x,y=yt3), color="gray20")
```

http://sape.inf.usi.ch/quick-reference/ggplot2/colour 
https://github.com/tidyverse/googlesheets4 
```{r eval=FALSE}
install.packages("googlesheets4")
library(googlesheets4)
url <- "https://docs.google.com/spreadsheets/d/1Le_A8n8LUNnPUQvdawnMw1ULmdLiuLaV-XPABvZFIGg"
exam <- read_sheet(url)
names(exam)
exam$`1a`
for(name in names(exam)){
  print(name)
  print(sum(exam[[name]][!is.na(exam[name])]==0)/length(exam[[name]][!is.na(exam[name])]))
}
```