Contingency Tables Quiz

PDF page 211: A two-way table provides a way of portraying data that can facilitate calculating probabilities. When used to calculate probabilities, a two-way table is often called a contingency table. The table helps in determining conditional probabilities quite easily. The table displays sample values in relation to two different variables that may be dependent or contingent on one another. We used two-way tables in Chapters 1 and 2 to calculate marginal and conditional distributions. These tables organize data in a way that supports the calculation of relative frequency and, therefore, experimental (empirical) probability. Later on, we will use contingency tables again, but in another manner.

PDF page 211: A two-way table provides a way of portraying data that can facilitate calculating probabilities. When used to calculate probabilities, a two-way table is often called a contingency table. The table helps in determining conditional probabilities quite easily. The table displays sample values in relation to two different variables that may be dependent or contingent on one another. We used two-way tables in Chapters 1 and 2 to calculate marginal and conditional distributions. These tables organize data in a way that supports the calculation of relative frequency and, therefore, experimental (empirical) probability. Later on, we will use contingency tables again, but in another manner.

PDF page 212: Speeding Violation in the No Speeding Violation in the Total Last Year Last Year Uses a cell phone while 25 280 305 driving Does not use a cell phone 45 405 450 while driving Total 70 685 755

PDF page 212: The total number of people in the sample is 755. The row totals are 305 and 450. The column totals are 70 and

PDF page 212: Speeding Violation in the No Speeding Violation in the Total Last Year Last Year Uses a cell phone while 25 280 305 driving Does not use a cell phone 45 405 450 while driving Total 70 685 755

PDF page 212: 305 = ≈ .4040 P⎝Person uses a cell phone while driving⎠ = number in study 755

PDF page 212: = ≈ .9073. P⎝Person had no violation in the last year⎠ = number in study 755

PDF page 212: number who had no violation AND uses cell phone while driving P(Person had no violation in the last year AND uses a cell phone while driving) = number in study 280 = 755 ≈ .3709

PDF page 213: number who used cell phone AND had a violation (Person uses a cell phone while driving GIVEN the person had a violation in the last year) = number in study who had a violation in the last year 25 = 70 ≈ .3571

PDF page 213: ⎞ 405 = .9 P⎝Person had no violation last year GIVEN person does not use cell phone while driving⎠ = 450

PDF page 212: e. This is a conditional probability. You are given that the person had no violation in the last year, so you need

PDF page 212: only consider the values in that column of data.

PDF page 214: Female 18 16 11 45 Male 16 25 14 55 Total 34 41 25 100

PDF page 213: a. There are 45 females in the sample; 18 prefer the coastline and 16 prefer hiking near lakes and streams. So, we

PDF page 213: know there are 45 − 18 − 16 = 11 female students who prefer hiking on mountain peaks. Continue reasoning in this way to complete the table.

PDF page 214: Female 18 16 11 45 Male 16 25 14 55 Total 34 41 25 100