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Mathematics calculas formulas, Exercises of Mathematics

Math formulas for the field in calculas, useful formulas also techiniques during the calculations

Typology: Exercises

2017/2018

Uploaded on 01/21/2018

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Revision for Midterm 2
Chapter 4: Probability
(1) Methods of Assigning Probabilities:
(a) Classical Method: when the probabilities are assigned based on laws or rules.
In this case, the probability of an event Ein a sample space Sis
P(E) = #(E)
#(S)·
Examples:
Probability to draw a card of hearts from a 52-card deck.
Probability that at least two students in the class celebrate their anniversary
on the same day.
(b) Relative Frequency of Occurrence: when the assignment of probabilities is based on
historical data.
In this case, the probability of an event Ein a sample space Sis
P(E) = Number of times the event Ehas occurred
Total number of opportunities for the event to occur·
Examples:
Probability to be hit by a lightning.
Probability to get injured at work.
(c) Subjective probability: when the assignment of probabilities is based on feelings,
knowledge and/or past experiences of a person or a group of people.
Examples:
A financial advisor tells there are 75% chance that a major financial crisis
happens within the next five years.
A taxi driver asserts there are 80% chance a route will be faster than another
one.
(2) Counting the Probabilities:
Different methods for computing the numbers of elements in Eand S:P(E) = #(E)
#(S).
(a) The mn-Counting Rule: Suppose a procedure can be realized in a sequence of k
(independent) steps. If the i-th step offer nipossibilities, for all i= 1,2, . . . , n, then
the procedure can be realized in
n1n2n3· · · nk
different ways.
Example:
In a certain country, all license plates consist of three letters (A to Z), followed by
three digits (0 to 9). How many different plates are there?
Solution: There are 26 26 26 10 10 10 = 17,576,000 different plates.
(b) Combinations: Suppose there are ndifferent items. The number of ways to select
r(with 0rn) different items is
nCr=n!
r!(nr)!·
Examples:
A box contains 30 chips, 5 of them being defective. If 10 of these 30 chips are
selected, in how many ways can exactly 3 of the 5 defective chips be selected?
Solution: This can be seen as a 2-step process; we select 3 of the 5 defective
chips (5C3), and then 7 of the 25 intact ones (25C7). By the mn-Counting, this
can be done in 5C3·25 C7= 4,807,000 ways.
Find the number of distinguishable permutations of the given letters MISSIS-
SIPPI”.
Solution: Writing an anagram with the letters of the word MISSISSIPPI con-
sists in filling 11 positions in 4 steps:
- Choose 1 position for the M: 11 C1= 11 possibilities
- Choose 4 positons among the 10 remaining positions for the I’s: 10C4= 210
possibilities
- Choose 4 positions among the 6 remaining positions for the S’s: 6C4= 15
possibilities
- Choose 2 positions among the 2 remaining positions for the P’s: 2C2= 1
possibilities
By the mn-Counting Rule, this can be done in 11210 151 = 34,650 different
ways.
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Revision for Midterm 2

Chapter 4: Probability

(1) Methods of Assigning Probabilities:

(a) Classical Method: when the probabilities are assigned based on laws or rules. In this case, the probability of an event E in a sample space S is

P (E) =

#(E)

#(S)

Examples:

  • Probability to draw a card of hearts from a 52-card deck.
  • Probability that at least two students in the class celebrate their anniversary on the same day.

(b) Relative Frequency of Occurrence: when the assignment of probabilities is based on historical data. In this case, the probability of an event E in a sample space S is

P (E) =

Number of times the event E has occurred Total number of opportunities for the event to occur

Examples:

  • Probability to be hit by a lightning.
  • Probability to get injured at work.

(c) Subjective probability: when the assignment of probabilities is based on feelings, knowledge and/or past experiences of a person or a group of people. Examples:

  • A financial advisor tells there are 75% chance that a major financial crisis happens within the next five years.
  • A taxi driver asserts there are 80% chance a route will be faster than another one.

(2) Counting the Probabilities:

Different methods for computing the numbers of elements in E and S: P (E) =

#(E)

#(S)

(a) The mn-Counting Rule: Suppose a procedure can be realized in a sequence of k (independent) steps. If the i-th step offer ni possibilities, for all i = 1, 2 ,... , n, then the procedure can be realized in n 1 n 2 n 3 · · · nk different ways.

Example: In a certain country, all license plates consist of three letters (A to Z), followed by three digits (0 to 9). How many different plates are there? Solution: There are 26 ∗ 26 ∗ 26 ∗ 10 ∗ 10 ∗ 10 = 17, 576 , 000 different plates.

(b) Combinations: Suppose there are n different items. The number of ways to select r (with 0 ≤ r ≤ n) different items is

nCr =^

n! r!(n − r)!

Examples:

  • A box contains 30 chips, 5 of them being defective. If 10 of these 30 chips are selected, in how many ways can exactly 3 of the 5 defective chips be selected? Solution: This can be seen as a 2-step process; we select 3 of the 5 defective chips ( 5 C 3 ), and then 7 of the 25 intact ones ( 25 C 7 ). By the mn-Counting, this can be done in 5 C 3 · 25 C 7 = 4, 807 , 000 ways.
  • Find the number of distinguishable permutations of the given letters MISSIS- SIPPI”. Solution: Writing an anagram with the letters of the word MISSISSIPPI con- sists in filling 11 positions in 4 steps:
    • Choose 1 position for the M: 11 C 1 = 11 possibilities
    • Choose 4 positons among the 10 remaining positions for the I’s: 10 C 4 = 210 possibilities
    • Choose 4 positions among the 6 remaining positions for the S’s: 6 C 4 = 15 possibilities
    • Choose 2 positions among the 2 remaining positions for the P’s: 2 C 2 = 1 possibilities By the mn-Counting Rule, this can be done in 11 ∗ 210 ∗ 15 ∗1 = 34, 650 different ways.

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(c) Permutations: Suppose there are n different items. The number of ways to select and order r (with 0 ≤ r ≤ n) different items is

nPr =^

n! (n − r)!

Examples:

  • In a certain country, all license plates consists of three letters (A to Z), followed by three digits (0 to 9). How many different plates consists of 3 different letters and 3 different digits? Solution: We must select and order 3 letters ( 26 P 3 ), and then select and order 3 digits ( 10 P 3 ). This gives a total of 26 P 3 ∗ 10 P 3 = 11, 232 , 000 plates with distinct letters and digits.
  • There are 4 accounting textbooks and 6 marketing textbooks in a box. You would like to place these 10 textbooks on a shelf, but there is only enough space for 8 of them. In how many ways can you: (i) Place 8 of your textbooks on the shelf if the order matters? Solution: There are 10 P 8 = 1, 814 , 400 ways to select 8 of the 10 books and order them on the shelf. (ii) Place 2 accounting textbooks and your 6 marketing textbooks on the shelf if the accounting textbooks must be to the left of the marketing textbooks? Solution: There are 4 P 2 = 12 ways to select and order the accounting textbooks, and 6 P 6 = 720 to order the marketing textbooks, for a total of 12 ∗ 720 = 8, 640 possible arrangements. (iii) Select 2 accounting textbooks, 6 marketing textbooks, and order these textbooks in any way? Solution: There are 4 C 2 = 6 ways to select 2 accounting textbooks and 6 C 6 = 1^ way to select the 6 marketing textbook. Finally, there are^8 P 8 = 8! = 40, 320 ways to order these 8 textbooks. So, there are 6 ∗ 1 ∗ 40 , 320 = 241 , 920 possible arrangements.

(3) Marginal, Joint, Union and Conditional Probabilities: Let S be a sample space and E, F be two events. (a) The marginal probability of E is P (E) = #(#(ES)). (b) The joint probability of E and F is

P (E ∩ F ) =

#(E ∩ F )

#(S)

where E ∩ F = {x ∈ S | x ∈ E and x ∈ F }. (c) The union probability of E and F is

P (E ∪ F ) =

#(E ∪ F )

#(S)

where E ∪ F = {x ∈ S | x ∈ E or x ∈ F }. (d) The (conditional) probability that E will occur given that F has occured is

P (E|F ) =

#(E ∩ F )

#(F )

Definitions:

  • Two events E and F are mutually exclusive if E ∩ F = {}.
  • Two events E and F are independent if P (E|F ) = P (E) and P (F |E) = P (F ).

Some Laws:

Law of Addition: P (E ∪ F ) = P (E) + P (F ) − P (E ∩ F ), or P (E ∩ F ) = P (E) + P (F ) − P (E ∪ F )

Law of Multiplication: P (E|F )P (F ) = P (E ∩ F ) = P (F |E)P (E)

Law of Conditional Probability: P (E|F ) =

P (E ∩ F )

P (F )

P (F |E)P (E)

P (F )

If E 1 , E 2 ,... , En and mutually exclusive and collectively exhaustive events, then

P (F ) = P (F ∩ E 1 ) + P (F ∩ E 2 ) + · · · + P (F ∩ En).