P(king I card is a face card) Are the events "king" and "face card independent

A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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2. Two dice are rolled. Find the probabilities of the following, as reduced fractions, and justify. Use the formula sheet if needed for help.

a. P(king I card is a face card) Are the events "king" and "face card independent? 

Basic Probability Principle
P(E) = n(s)
Product Rule
P(EnF) = P(E) · P(FE) = P(F) · P(E|F)
Union Rule
For sets: n(AUB) = n(A) + n(B) - n(ANB)
For probability: P(EUF) = P(E) + P(F) − P(E^F)
Complement Rule (Probability)
P(E') = 1 - P(E)
P(E) = 1 - P(E')
Complement Rule (Number of Outcomes)
n(E) = n(S) - n(E')
n(E') = n(S) — n(E)
Permutations
P(n, k)
Bayes' Theorem
P(F;).P(E|F;)
P(F;|E) = P(F1).P(E|F1) + P(F2)·P(E|F2) + ... + P(Fn)·P(E|Fn)
P(F).P(EF)
Special Case: P(F|E) = P(F).P(E|F)+P(F').P(E\F')
n!
(n-k)!
Conditional Probability
n(EnF) P(ENF)
P(F)
n(F)
Distinguishable Permutations
n!
n₁!n₂!...nk!
P(E|F) =
=
Expected Value
E(x) = x₁p₁ + x2P2 +
·+XnPn
Binomial Probability
P(k successes in n trials) = C(n. k)p(1-p)"-h
...
Combinations
C(n, k) = k!(n-k)!
Expected # of Successes of a Binomial
or Combination-based Random Variable
E(x) = np
=
2
Odds
Odds in favor of E=
If odds in favor of E are m:n,
then P(E)
m
m+n
Number of subsets
If a set has n elements,
then it has 2" subsets.
=
P(E)
P(E')
Independent Events
P(E|F) = P(E)
P(F|E) = P(F)
P(EnF) = P(E). P(F)
Table of Outcomes for Rolling 2 Dice
1
2
3
6
4 5
1|(1,1) (1,2) (1,3) (1,4) (1,5) (1,6)
2 (2,1) (2,2) (2,3) (2,4) (2,5) (2,6)
3 (3,1) (3,2) (3,3) (3,4) (3,5) (3,6)
4 (4,1) (4,2) (4,3) (4,4) (4,5) (4,6)
5 (5,1) (5,2) (5.3) (5,4) (5,5) (5,6)
6(6,1) (6,2) (6,3) (6,4) (6,5) (6,6)
Table of Sums when Rolling 2 Dice
2 3 4 5 6
5 6
6 7 8
1
1 2 3 4
2
3 4
5
3 4 5
6
7 8 9
4 5 6
7
8 9 10
5 6 7
8
9 10 11
6 7 8
9 10 11 12
Irod
Transcribed Image Text:Basic Probability Principle P(E) = n(s) Product Rule P(EnF) = P(E) · P(FE) = P(F) · P(E|F) Union Rule For sets: n(AUB) = n(A) + n(B) - n(ANB) For probability: P(EUF) = P(E) + P(F) − P(E^F) Complement Rule (Probability) P(E') = 1 - P(E) P(E) = 1 - P(E') Complement Rule (Number of Outcomes) n(E) = n(S) - n(E') n(E') = n(S) — n(E) Permutations P(n, k) Bayes' Theorem P(F;).P(E|F;) P(F;|E) = P(F1).P(E|F1) + P(F2)·P(E|F2) + ... + P(Fn)·P(E|Fn) P(F).P(EF) Special Case: P(F|E) = P(F).P(E|F)+P(F').P(E\F') n! (n-k)! Conditional Probability n(EnF) P(ENF) P(F) n(F) Distinguishable Permutations n! n₁!n₂!...nk! P(E|F) = = Expected Value E(x) = x₁p₁ + x2P2 + ·+XnPn Binomial Probability P(k successes in n trials) = C(n. k)p(1-p)"-h ... Combinations C(n, k) = k!(n-k)! Expected # of Successes of a Binomial or Combination-based Random Variable E(x) = np = 2 Odds Odds in favor of E= If odds in favor of E are m:n, then P(E) m m+n Number of subsets If a set has n elements, then it has 2" subsets. = P(E) P(E') Independent Events P(E|F) = P(E) P(F|E) = P(F) P(EnF) = P(E). P(F) Table of Outcomes for Rolling 2 Dice 1 2 3 6 4 5 1|(1,1) (1,2) (1,3) (1,4) (1,5) (1,6) 2 (2,1) (2,2) (2,3) (2,4) (2,5) (2,6) 3 (3,1) (3,2) (3,3) (3,4) (3,5) (3,6) 4 (4,1) (4,2) (4,3) (4,4) (4,5) (4,6) 5 (5,1) (5,2) (5.3) (5,4) (5,5) (5,6) 6(6,1) (6,2) (6,3) (6,4) (6,5) (6,6) Table of Sums when Rolling 2 Dice 2 3 4 5 6 5 6 6 7 8 1 1 2 3 4 2 3 4 5 3 4 5 6 7 8 9 4 5 6 7 8 9 10 5 6 7 8 9 10 11 6 7 8 9 10 11 12 Irod
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