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This module introduces the contingency table as a way of determining conditional probabilities.

A contingency table provides a way of portraying data that can facilitate calculating probabilities. 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. Later on, we will use contingency tables again, but in another manner. Contingincy tables provide a way of portraying data that can facilitate calculating probabilities.

Suppose a study of speeding violations and drivers who use car phones produced the following fictional data:

Speeding violation in the last year No speeding violation in the last year Total
Car phone user 25 280 305
Not a car phone user 45 405 450
Total 70 685 755

The total number of people in the sample is 755. The row totals are 305 and 450. The column totals are 70 and 685. Notice that 305 + 450 = 755 and 70 + 685 = 755 .

Calculate the following probabilities using the table

P(person is a car phone user) =

number of car phone users total number in study = 305 755

P(person had no violation in the last year) =

number that had no violation total number in study = 685 755

P(person had no violation in the last year AND was a car phone user) =

280 755

P(person is a car phone user OR person had no violation in the last year) =

( 305 755 + 685 755 ) - 280 755 = 710 755

P(person is a car phone user GIVEN person had a violation in the last year) =

25 70 (The sample space is reduced to the number of persons who had a violation.)

P(person had no violation last year GIVEN person was not a car phone user) =

405 450 (The sample space is reduced to the number of persons who were not car phone users.)

The following table shows a random sample of 100 hikers and the areas of hiking preferred:

Hiking area preference
Sex The Coastline Near Lakes and Streams On Mountain Peaks Total
Female 18 16 ___ 45
Male ___ ___ 14 55
Total ___ 41 ___ ___

Complete the table.

Hiking area preference
Sex The Coastline Near Lakes and Streams On Mountain Peaks Total
Female 18 16 11 45
Male 16 25 14 55
Total 34 41 25 100

Are the events "being female" and "preferring the coastline" independent events?

Let F = being female and let C = preferring the coastline.

  • P(F AND C) =
  • P(F) P(C) =

Are these two numbers the same? If they are, then F and C are independent. If they are not, then F and C are not independent.

  • P(F AND C) = 18 100 = 0.18
  • P(F) P(C) = 45 100 34 100 = 0.45 0.34 = 0.153

P(F AND C) P(F) P(C) , so the events F and C are not independent.

Find the probability that a person is male given that the person prefers hiking near lakes and streams. Let M = being male and let L = prefers hiking near lakes and streams.

  • What word tells you this is a conditional?
  • Fill in the blanks and calculate the probability: P(___|___) = ___ .
  • Is the sample space for this problem all 100 hikers? If not, what is it?
  • The word 'given' tells you that this is a conditional.
  • P(M|L) = 25 41
  • No, the sample space for this problem is 41.

Find the probability that a person is female or prefers hiking on mountain peaks. Let F = being female and let P = prefers mountain peaks.

  • P(F) =
  • P(P) =
  • P(F AND P) =
  • Therefore, P(F OR P) =
  • P(F) = 45 100
  • P(P) = 25 100
  • P(F AND P) = 11 100
  • P(F OR P) = 45 100 + 25 100 - 11 100 = 59 100

Muddy Mouse lives in a cage with 3 doors. If Muddy goes out the first door, the probability that he gets caught by Alissa the cat is 1 5 and the probability he is not caught is 4 5 . If he goes out the second door, the probability he gets caught by Alissa is 1 4 and the probability he is not caught is 3 4 . The probability that Alissa catches Muddy coming out of the third door is 1 2 and the probability she does not catch Muddy is 1 2 . It is equally likely that Muddy will choose any of the three doors so the probability of choosing each door is 1 3 .

Door choice
Caught or Not Door One Door Two Door Three Total
Caught 1 15 1 12 1 6 ____
Not Caught 4 15 3 12 1 6 ____
Total ____ ____ ____ 1
  • The first entry 1 15 = ( 1 5 ) ( 1 3 ) is P(Door One AND Caught) .
  • The entry 4 15 = ( 4 5 ) ( 1 3 ) is P(Door One AND Not Caught) .

Verify the remaining entries.

Complete the probability contingency table. Calculate the entries for the totals. Verify that the lower-right corner entry is 1.

Door choice
Caught or Not Door One Door Two Door Three Total
Caught 1 15 1 12 1 6 19 60
Not Caught 4 15 3 12 1 6 41 60
Total 5 15 4 12 2 6 1

What is the probability that Alissa does not catch Muddy?

41 60

What is the probability that Muddy chooses Door One OR Door Two given that Muddy is caught by Alissa?

9 19

You could also do this problem by using a probability tree. See the Tree Diagrams (Optional) section of this chapter for examples.

Questions & Answers

are nano particles real
Missy Reply
yeah
Joseph
Hello, if I study Physics teacher in bachelor, can I study Nanotechnology in master?
Lale Reply
no can't
Lohitha
where we get a research paper on Nano chemistry....?
Maira Reply
nanopartical of organic/inorganic / physical chemistry , pdf / thesis / review
Ali
what are the products of Nano chemistry?
Maira Reply
There are lots of products of nano chemistry... Like nano coatings.....carbon fiber.. And lots of others..
learn
Even nanotechnology is pretty much all about chemistry... Its the chemistry on quantum or atomic level
learn
Google
da
no nanotechnology is also a part of physics and maths it requires angle formulas and some pressure regarding concepts
Bhagvanji
hey
Giriraj
Preparation and Applications of Nanomaterial for Drug Delivery
Hafiz Reply
revolt
da
Application of nanotechnology in medicine
has a lot of application modern world
Kamaluddeen
yes
narayan
what is variations in raman spectra for nanomaterials
Jyoti Reply
ya I also want to know the raman spectra
Bhagvanji
I only see partial conversation and what's the question here!
Crow Reply
what about nanotechnology for water purification
RAW Reply
please someone correct me if I'm wrong but I think one can use nanoparticles, specially silver nanoparticles for water treatment.
Damian
yes that's correct
Professor
I think
Professor
Nasa has use it in the 60's, copper as water purification in the moon travel.
Alexandre
nanocopper obvius
Alexandre
what is the stm
Brian Reply
is there industrial application of fullrenes. What is the method to prepare fullrene on large scale.?
Rafiq
industrial application...? mmm I think on the medical side as drug carrier, but you should go deeper on your research, I may be wrong
Damian
How we are making nano material?
LITNING Reply
what is a peer
LITNING Reply
What is meant by 'nano scale'?
LITNING Reply
What is STMs full form?
LITNING
scanning tunneling microscope
Sahil
how nano science is used for hydrophobicity
Santosh
Do u think that Graphene and Fullrene fiber can be used to make Air Plane body structure the lightest and strongest. Rafiq
Rafiq
what is differents between GO and RGO?
Mahi
what is simplest way to understand the applications of nano robots used to detect the cancer affected cell of human body.? How this robot is carried to required site of body cell.? what will be the carrier material and how can be detected that correct delivery of drug is done Rafiq
Rafiq
if virus is killing to make ARTIFICIAL DNA OF GRAPHENE FOR KILLED THE VIRUS .THIS IS OUR ASSUMPTION
Anam
analytical skills graphene is prepared to kill any type viruses .
Anam
Any one who tell me about Preparation and application of Nanomaterial for drug Delivery
Hafiz
what is Nano technology ?
Bob Reply
write examples of Nano molecule?
Bob
The nanotechnology is as new science, to scale nanometric
brayan
nanotechnology is the study, desing, synthesis, manipulation and application of materials and functional systems through control of matter at nanoscale
Damian
Is there any normative that regulates the use of silver nanoparticles?
Damian Reply
what king of growth are you checking .?
Renato
Difference between extinct and extici spicies
Amanpreet Reply
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Source:  OpenStax, Collaborative statistics for mt230. OpenStax CNX. Aug 18, 2011 Download for free at http://legacy.cnx.org/content/col11345/1.2
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