A random sample of cars was taken and various measurements were recorded regarding the cars.
The data can be seen below.
## type price mpgCity driveTrain passengers weight MPG
## 1 small 15.9 25 front 5 2705 mpg < 23
## 2 midsize 33.9 18 front 5 3560 mpg < 23
## 3 midsize 37.7 19 front 6 3405 mpg < 23
## 4 midsize 30.0 22 rear 4 3640 mpg < 23
## 5 midsize 15.7 22 front 6 2880 mpg < 23
## 6 large 20.8 19 front 6 3470 mpg < 23
Afterwards, the data was condensed into a contingency table.
##
## mpg < 23 mpg >= 23
## large 11 0
## midsize 22 0
## small 16 5
Suppose we were interested in knowing if there is a difference in gas mileage between small, midsize, and large cars.
The following data was pulled from a college statistics class. 164 students had both their midterm grade and their class section number recorded. See the first ten students below.
## Midterm1 Section
## 1 67 a
## 2 59 a
## 3 100 a
## 4 81 a
## 5 80 a
## 6 63 a
The data was then further condensed into a contingency table displaying the number of students in each section that passed or failed the midterm. See below.
##
## fail pass
## a 22 36
## b 25 30
## c 12 39
Suppose we were interested in knowing whether there was a big difference in ‘pass rates’ between different class sections (the percent of students who passed the test).
Let’s say I want to make a bet with you. I give you a 6 sided die and tell you that if you roll a ‘One’ you pay me $10. If you roll a ‘Four’, ‘Five’, or ‘Six’, I pay you $10. You suspect some funny business so you say you will only do it if I will first roll the dice 60 times and record the outcomes so you can look at the data. I agree and record the results below.
## draws
## Five Four One Six Three Two
## 6 8 16 9 9 12