Sunday, October 1, 2023

Appendix A - Infinite Series

In the previous section, we completed a discussion on probability. In this appendix A, we will see Infinite series.

• In chapter 9, we discussed sequences and series.
1. Consider the sequence given below:
$a_1, a_2, a_3,~.~.~.~,~a_n,~.~.~.$
• This sequence has infinite number of terms. So it is called an infinite sequence.
2. Let us write the corresponding series:
$a_1~+~a_2~+~a_3~+~.~.~.~,~+~a_n~+~.~.~.$
• This series is called the infinite series associated with the infinite sequence.
3. We can abbreviate an infinite series as shown below:
$a_1~+~a_2~+~a_3~+~.~.~.~,~+~a_n~+~.~.~.~=~\sum\limits_{i=1}^{i=\infty} a_i$


• In chapter 8, we discussed binomial theorem. Based on that theorem, we derived the formula:
$(1+x)^n~=~{}^n \rm{C}_0~+~{}^n \rm{C}_1 x~+~{}^n \rm{C}_2 x^2~+~{}^n \rm{C}_3 x^3~+~.~.~.~+~{}^n \rm{C}_n x^n$
• "n" in the above formula must be an integer. Also, it should not be -ve. This is because, in such cases, we will not be able to calculate ${}^n \rm{C}_r$.
• We will now see a formula which can be used when n is not an integer and/or n is -ve. It can be explained in 4 steps:
1. The formula is:
$(1+x)^m~=~1~+~mx~+~{\frac{m(m-1)}{1 \times 2}}x^2~+~{\frac{m(m-1)(m-2)}{1 \times 2 \times 3}}x^3~+~{\frac{m(m-1)(m-2)(m-3)}{1 \times 2 \times 3 \times 4}}x^4~+~.~.~.$
• We will see the derivation of this formula in higher classes.
2. This formula is applicable whenever |x| < 1
• This condition can be explained in 5 steps:
(i) Consider the value of x. Based on that value, we can mark it’s position on the number line.
(ii) The distance of this mark from zero must be less than 1.
(iii) So, if x is -ve,
    ♦ The mark must not be on -1.
    ♦ The mark must not be anywhere to the left of -1.
(iv) Similarly, if x is +ve,
    ♦ The mark must not be on 1.
    ♦ The mark must not be anywhere to the right of 1.
(v) We can combine the above four points as:
-1 < x < 1

• The importance of this condition will become clear when we see an example. Let us put “-3” in the place of x and "-2" in the place of m. We get:

$\begin{array}{ll}{}    &{(1-3)^{-2}}    & {~=~}    & {1 + (-2)(-3) + \frac{(-2)(-3-1)}{1 \times 2} (-3)^2 + \frac{(-2)(-3-1)(-3-2)}{1 \times 2 \times 3} (-3)^3 + . . .}    &{} \\
{\Rightarrow}    &{(-2)^{-2}}    & {~=~}    & {1 + 6 + \frac{(-2)(-4)}{2} (9) + \frac{(-2)(-4)(-5)}{6} (-27) + . . .}    &{} \\
{\Rightarrow}    &{(-1)^{-2} \times (2)^{-2}}    & {~=~}    & {1 + 6 + \frac{8}{2} (9) + \frac{-40}{6} (-27) + . . .}    &{} \\
{\Rightarrow}    &{1 \times \frac{1}{4}}    & {~=~}    & {1 + 6 + (4) (9) + \frac{-20}{3} (-27) + . . .}    &{} \\
{\Rightarrow}    &{\frac{1}{4}}    & {~=~}    & {1 + 6 + 36 + 180 + . . .}    &{} \\
\end{array}$

• This is not possible. So before applying this formula, we must make sure that -1 < x < 1.

3. We know how to expand (a+b)m when m is a +ve integer. But what if m is not an integer and/or -ve?
In such cases, we can use the above formula. This is shown below:

$\begin{array}{ll}{}    &{(a+b)^m}    & {~=~}    & {\left[a \left(1 + \frac{b}{a} \right) \right]^m}    &{} \\
{}    &{}    & {~=~}    & {a^m \left(1 + \frac{b}{a} \right)^m}    &{} \\
{}    &{}    & {~=~}    & {a^m \left[1 + m{\frac{b}{a}} + {\frac{m(m-1)}{1 \times 2}}\left(\frac{b}{a} \right)^2 + {\frac{m(m-1)(m-2)}{1 \times 2 \times 3}}\left(\frac{b}{a} \right)^3~+~.~.~. \right]}    &{} \\
{}    &{}    & {~=~}    & {a^m + m a^{m-1} b + {\frac{m(m-1)}{1 \times 2}}a^{m-2} b^2 + {\frac{m(m-1)(m-2)}{1 \times 2 \times 3}}a^{m-3} b^3 ~+~.~.~.}    &{} \\
\end{array}$

• We were able to use the formula because we wrote (a+b)m as $\left[a \left(1 + \frac{b}{a} \right) \right]^m$.
• Recall that, to use the formula, |x| must be less than 1.
• So in our present case, $\left| \frac{b}{a} \right| $ must be less than 1.
• This can be explained in 5 steps:
(i) Values of a and b:
    ♦ a can be +ve or -ve. It can be any real number.
    ♦ b can be +ve or -ve. It can be any real number.
(ii) Calculating $\frac{b}{a}$:
We calculate $\frac{b}{a}$ using the proper signs.
(iii) Marking the position on the number line:
We mark $\frac{b}{a}$ based on the result in (ii).
(iv) The mark can be either on the left side or right side of zero. But it's distance from zero must be less than 1.

Let us see some examples:
Example1:
• Put a = 2 and b = -3
• Then $\frac{b}{a} = \frac{-3}{2}$ = -1.5
• When we mark $\frac{b}{a}$ on the number line, it will be at a distance of 1.5 units from zero. So we will not be able to use the formula.

Example2:
• Put a = 4 and b = -3
• Then $\frac{b}{a} = \frac{-3}{4}$ = -0.75
• When we mark $\frac{b}{a}$ on the number line, it will be at a distance of 0.75 units from zero. So we can use the formula

(v) Based on the above four steps, we can write:
$\frac{b}{a}$ must be a proper fraction. It can be +ve or -ve.

4. Based on the expansion in (3), we can write the general term in the expansion. It is given below:

$$\frac{m(m-1)(m-2)(m-3)~.~.~.~(m-r+1) a^{m-r} b^r}{1 \times 2 \times 3 \times ~.~.~.\times r}$$


Based on the formula that we wrote in (1), we can derive four useful results:

Result I:
$\begin{array}{ll}{}    &{(1+x)^{-1}}    & {~=~}    &{1 + (-1)x + \frac{(-1)(-1-1)}{1 \times 2} x^2 + \frac{(-1)(-1-1)(-1-2)}{1 \times 2 \times 3} x^3~+~.~.~.}    &{} \\
{}    &{}    & {~=~}    &{1 + (-1)x + \frac{(-1)(-2)}{1 \times 2} x^2 + \frac{(-1)(-2)(-3)}{1 \times 2 \times 3} x^3~+~.~.~.}    &{} \\
{}    &{}    & {~=~}    &{1 + (-1)x + \frac{(-1)(-1)}{1 \times 1} x^2 + \frac{(-1)(-1)(-1)}{1 \times 1 \times 1} x^3~+~.~.~.}    &{} \\
{}    &{}    & {~=~}    &{1 - x + x^2 – x^3~+~.~.~.}    &{} \\
\end{array}$

Result II:                

$\begin{array}{ll}{}    &{(1-x)^{-1}}    & {~=~}    &{[1+(-x)]^{-1}}    &{} \\
{}    &{}    & {~=~}    &{1 + (-1)(-x) + \frac{(-1)(-1-1)}{1 \times 2} (-x)^2 + \frac{(-1)(-1-1)(-1-2)}{1 \times 2 \times 3} (-x)^3~+~.~.~.}    &{} \\
{}    &{}    & {~=~}    &{1 + (-1)(-x) + \frac{(-1)(-2)}{1 \times 2} (x^2) + \frac{(-1)(-2)(-3)}{1 \times 2 \times 3} (-1)(x^3)~+~.~.~.}    &{} \\
{}    &{}    & {~=~}    &{1 + (-1)(-x) + \frac{(-1)(-1)}{1 \times 1} (x^2) + \frac{(-1)(-1)(-1)}{1 \times 1 \times 1} (-1)(x^3)~+~.~.~.}    &{} \\
{}    &{}    & {~=~}    &{1 + x + x^2 + x^3~+~.~.~.}    &{} \\
\end{array}$

Result III:

$\begin{array}{ll}{}    &{(1+x)^{-2}}    & {~=~}    &{1 + (-2)x + \frac{(-2)(-2-1)}{1 \times 2} x^2 + \frac{(-2)(-2-1)(-2-2)}{1 \times 2 \times 3} x^3~+~.~.~.}    &{} \\
{}    &{}    & {~=~}    &{1 + (-2)x + \frac{(-2)(-3)}{1 \times 2} x^2 + \frac{(-2)(-3)(-4)}{1 \times 2 \times 3} x^3~+~.~.~.}    &{} \\
{}    &{}    & {~=~}    &{1 + (-2)x + \frac{(-1)(-3)}{1 \times 1} x^2 + \frac{(-1)(-1)(-4)}{1 \times 1 \times 1} x^3~+~.~.~.}    &{} \\
{}    &{}    & {~=~}    &{1 - 2x + 3 x^2 –4 x^3~+~.~.~.}    &{} \\
\end{array}$

Result IV:

$\begin{array}{ll}{}    &{(1-x)^{-2}}    & {~=~}    &{[1+(-x)]^{-2}}    &{} \\
{}    &{}    & {~=~}    &{1 + (-2)(-x) + \frac{(-2)(-2-1)}{1 \times 2} (-x)^2 + \frac{(-2)(-2-1)(-2-2)}{1 \times 2 \times 3} (-x)^3~+~.~.~.}    &{} \\
{}    &{}    & {~=~}    &{1 + (-2)(-x) + \frac{(-2)(-3)}{1 \times 2} (-x)^2 + \frac{(-2)(-3)(-4)}{1 \times 2 \times 3} (-x)^3~+~.~.~.}    &{} \\
{}    &{}    & {~=~}    &{1 + (-2)(-x) + \frac{(-1)(-3)}{1 \times 1} x^2 + \frac{(-1)(-1)(-4)}{1 \times 1 \times 1} (-1) x^3~+~.~.~.}    &{} \\
{}    &{}    & {~=~}    &{1 + 2x + 3x^2 + 4x^3~+~.~.~.}    &{} \\
\end{array}$


Now we will see a solved example:

Solved example 1
Expand $\left(1 - \frac{x}{2} \right)^{- \frac{1}{2}}$, when |x| < 2.
Solution:
1. We can rewrite the given expression as:
$\left[1 + \left(- \frac{x}{2} \right) \right]^{- \frac{1}{2}}$
• Consider the term $\left(- \frac{x}{2} \right)$.
We know that, this term must be less than 1 and at the same time, greater than -1. This condition will be satisfied only if |x| is less than 2. The reader must do the necessary analysis and become convinced about this fact.
2. Now we can write the expansion:

$\begin{array}{ll}{}    &{\left[1 + \left(- \frac{x}{2} \right) \right]^{- \frac{1}{2}}}    & {~=~}    &{1 + \left(-\frac{1}{2} \right) \left(-\frac{x}{2} \right) + \frac{\left(-\frac{1}{2} \right)\left(-\frac{1}{2} – 1 \right)}{1 \times 2} \left(-\frac{x}{2} \right)^2 + \frac{\left(-\frac{1}{2} \right)\left(-\frac{1}{2} – 1 \right)\left(-\frac{1}{2} – 2 \right)}{1 \times 2 \times 3} \left(-\frac{x}{2} \right)^3~+~.~.~.}    &{} \\
{}    &{}    & {~=~}    &{1 + \left(-\frac{1}{2} \right) \left(-\frac{x}{2} \right) + \frac{\left(-\frac{1}{2} \right)\left(-\frac{3}{2} \right)}{1 \times 2} \left(-\frac{x}{2} \right)^2 + \frac{\left(-\frac{1}{2} \right)\left(-\frac{3}{2} \right)\left(-\frac{5}{2} \right)}{1 \times 2 \times 3} \left(-\frac{x}{2} \right)^3~+~.~.~.}    &{} \\
{}    &{}    & {~=~}    &{1 + \left(-\frac{1}{2} \right) \left(-\frac{x}{2} \right) + \frac{3}{8} \left(-\frac{x}{2} \right)^2 + \frac{-5}{16} \left(-\frac{x}{2} \right)^3 ~+~.~.~.}    &{} \\
{}    &{}    & {~=~}    &{1 + \frac{x}{4} +\frac{3 x^2}{32} + \frac{5 x^3}{128} ~+~.~.~.}    &{} \\
\end{array}$


In the next section, we will see infinite geometric series.

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Saturday, September 23, 2023

16.9 - Miscellaneous Exercise on Axiomatic Probability

In the previous section, we completed a discussion on axiomatic probability. In this section, we will see some miscellaneous examples.

Solved example 16.14
On her vacations Veena visits four cities (A, B, C and D) in a random order. What is the probability that she visits (i) A before B? (ii) A before B and B before C? (iii) A first and B last? (iv) A either first or second? (v) A just before B?
Solution:
• The first visit can be any one of the four cities.
• The second visit can be any one of the remaining three cities.
• The third visit can be any one of the remaining two cities.
• The fourth visit will be only one remaining city.
• So there are (4 × 3 × 2 × 1) orders in which Veena can visit the four cities. In other words, there are 4! possible orders.
• 4! = 24. So the sample space will contain 24 elements. This is shown below:
S = {
ABCD,    ABDC,    ACBD,    ACDB,    ADBC,    ADCB,
BACD,    BADC,    BCAD,    BCDA,    BDAC,    BDCA,   
CABD,    CADB,    CBAD,    CBDA,    CDAB,    CDBA,
DABC,    DACB,    DBAC,    DBCA,    DCAB,    DCBA
}
• The 24 elements of the sample space can be easily written using the fig.16.3 below:

Fig.16.3

• Since there are 24 elements in S, we can write:
n(S) = 24

Part (i):
1. Let E be the event: She visits A before B.
Let us write the favorable outcomes for E:
• In the first row of S, A comes first in all six cases. So we have 6 from the first row.
• In the second row, B comes first in all six cases. So we have 0 from the second row.
• In the third row, A comes before B in three cases. So we have 3 from the third row.
   ♦ They are: CABD,    CADB,     CDAB
• In the fourth row, A comes before B in three cases. So we have 3 from the third row.
   ♦ They are: DABC,    DACB,     DCAB
• So total number of favorable outcomes =
6 + 0 + 3 + 3 = 12
• We can write: n(E) = 12
2. Since all outcomes in S are equally likely, we get:
$\rm{P(E) = \frac{n(E)}{n(S)} = \frac{12}{24} = \frac{1}{2}}$

Part (ii):
1. Let F be the event: She visits A before B and B before C.
Let us write the favorable outcomes for F:
• In the first row of S, the required order is available in 3 cases. So we have 3 from the first row.
   ♦ They are: ABCD,    ABDC,    ADBC
• In the second row, B comes first in all 6 cases. So we have 0 from the second row.
• In the third row, C comes first in all 6 cases. So we have 0 from the third row.
• In the fourth row, the required order is available in 1 case. So we have 1 from the fourth row.
   ♦ It is: DABC
• So total number of favorable outcomes =
3 + 1 = 4
• We can write: n(F) = 4
2. Since all outcomes in S are equally likely, we get:
$\rm{P(F) = \frac{n(F)}{n(S)} = \frac{4}{24} = \frac{1}{6}}$

Part (iii):
1. Let G be the event: She visits A first and B last.
Let us write the favorable outcomes for G
• In the first row of S, the required order is available in 2 cases. So we have 2 from the first row.
   ♦ They are:  ACDB,    ADCB
• In the second row, B comes first in all 6 cases. So we have 0 from the second row.
• In the third row, C comes first in all 6 cases. So we have 0 from the third row.
• In the fourth row, D comes first in all 6 cases. So we have 0 from the fourth row.
• So total number of favorable outcomes = 2
• We can write: n(G) = 2
2. Since all outcomes in S are equally likely, we get:
$\rm{P(G) = \frac{n(G)}{n(S)} = \frac{2}{24} = \frac{1}{12}}$ 

Part (iv):
1. Let H be the event: She visits A either first or second.
Let us write the favorable outcomes for H
• In the first row of S, the required order is available in all 6 cases. So we have 6 from the first row.
• In the second row, A comes second in 2 cases. So we have 2 from the second row.
   ♦ They are: BACD,    BADC
• In the third row, A comes second in 2 cases. So we have 2 from the third row.
   ♦ They are: CABD,    CADB
• In the fourth row, A comes second in 2 cases. So we have 2 from the fourth row.
   ♦ They are: DABC,    DACB
• So total number of favorable outcomes =
6 + 2 + 2 + 2
• We can write: n(H) = 12
2. Since all outcomes in S are equally likely, we get:
$\rm{P(H) = \frac{n(H)}{n(S)} = \frac{12}{24} = \frac{1}{2}}$

Part (v):
1. Let I be the event: She visits A just before B.
Let us write the favorable outcomes for I
• In the first row of S, the required order is available in 2 cases. So we have 2 from the first row.
   ♦ They are: ABCD,    ABDC
• In the second row, the required order is not available in any of the 6 cases. So we have 0 from the second row.
• In the third row, the required order is available in 2 cases. So we have 2 from the third row.
   ♦ They are: CABD,     CDAB
• In the fourth row, the required order is available in 2 cases. So we have 2 from the fourth row.
   ♦ They are: DABC,     DCAB
• So total number of favorable outcomes =
2 +0 + 2 + 2
• We can write: n(I) = 6
2. Since all outcomes in S are equally likely, we get:
$\rm{P(I) = \frac{n(I)}{n(S)} = \frac{6}{24} = \frac{1}{4}}$

Solved example 16.15
Find the probability that when a hand of 7 cards is drawn from a well shuffled deck of 52 cards, it contains (i) all Kings (ii) 3 Kings (iii) atleast 3 Kings.
Solution:
• Number combinations of 7 cards is $\rm{{}^{52} C_{7}}$.
• So we can write: $\rm{n(S) = {}^{52}C_{7}}$ 

Part (i):
1. We can imagine two boxes.
• The left side box is for the four king cards. The right side box is for the remaining three cards.
• For filling the left side box, we must use only the four king cards. Number of possible combinations of four king cards, taking all four at a time is $\rm{{}^{4} C_{4}}$. So this box  can be filled in $\rm{{}^{4} C_{4}}$ ways.
• For filling the right side box, we must not use any of the four king cards. So the right side box can be filled in $\rm{{}^{48} C_{3}}$ ways.
• The two boxes can be filled together in
$\rm{{}^{4} C_{4}~\times~{}^{48} C_{3}}$ ways.
• Thus the number of combinations with all kings is:
$\rm{{}^{4} C_{4}~\times~{}^{48} C_{3}}$
• We can write:
If A is the event: “getting all the kings”, then:
$\rm{n(A) = {}^{4} C_{4}~\times~{}^{48} C_{3}}$
2. Since all outcomes in S are equally likely, we get:
$\rm{P(A) = \frac{n(A)}{n(S)} = \frac{{}^{4} C_{4}~\times~{}^{48} C_{3}}{{}^{52} C_{7}} = \frac{1}{7735}}$

Part (ii):
1. We can imagine two boxes.
• The left side box is for the three king cards. The right side box is for the remaining four cards.
• For filling the left side box, we must use only the four king cards. Number of possible combinations of four king cards, taking three at a time is $\rm{{}^{4} C_{3}}$. So this box  can be filled in $\rm{{}^{4} C_{3}}$ ways.
• For filling the right side box, we must not use any of the four king cards. Because, the combination must contain exactly three kings. So the right side box can be filled in $\rm{{}^{48} C_{4}}$ ways.
• The two boxes can be filled together in
$\rm{{}^{4} C_{3}~\times~{}^{48} C_{4}}$ ways.
• Thus the number of combinations with all kings is:
$\rm{{}^{4} C_{3}~\times~{}^{48} C_{4}}$
• We can write:
If B is the event: “getting exactly three kings”, then:
$\rm{n(B) = {}^{4} C_{3}~\times~{}^{48} C_{4}}$
2. Since all outcomes in S are equally likely, we get:
$\rm{P(B) = \frac{n(B)}{n(S)} = \frac{{}^{4} C_{3}~\times~{}^{48} C_{4}}{{}^{52} C_{7}} = \frac{9}{1547}}$

Part (iii):
1. Consider the two events A and B that we saw in parts (i) and (ii) respectively above.
   ♦ In A, each combination has exactly 4 kings.
   ♦ In B, each combination has exactly 3 kings.
• So A and B are mutually exclusive events.
2. Consider the set (A∪B).
When the outcome is from (A∪B), two things are possible:
(i) The outcome is from A. Then the condition “atleast 3 kings” is satisfied.
(ii) The outcome is from B. Then also the condition “atleast 3 kings” is satisfied.
3. So we want P(A∪B)
• We have: P(A∪B) = P(A) + P(B)
• Substituting the known values, we get:
P(A∪B) = $\frac{1}{7735} + \frac{9}{1547} = \frac{46}{7735}$

Solved example 16.16
If A, B, C are three events associated with a random experiment, prove that
P(A∪B∪C) = P(A) + P(B) +P(C) − P(A∩B) − P(A∩C) – P(B∩C) + P(A∩B∩C)
Solution:
1. Consider the LHS of the given expression.
• We can think of a new event (B∪C)
• Let E = (B∪C)
2. Now the LHS becomes:

$\begin{array}{ll}
{}&{\rm{P(A∪B∪C)}}
& {~=~}& {\rm{P(A∪E)}} &{} \\

{}&{}
& {~=~}& {\rm{P(A) + P(E) - P(A∩E)}} &{} \\

\end{array}$

3. Next step is to simplify the second term in the RHS of (2). The second term is P(E). We can write:

$\begin{array}{ll}
{}&{\rm{P(E)}}
& {~=~}& {\rm{P(B∪C)}} &{} \\

{}&{}
& {~=~}& {\rm{P(B) + P(C) - P(B∩C)}} &{} \\

\end{array}$

4. Next step is to simplify the third term in the RHS of (2). The third term is P(A∩E). We can write:

$\begin{array}{ll}
{}&{\rm{A∩E}}
& {~=~}& {\rm{A∩(B∪C)}}
&{} \\

{\Rightarrow}&{\rm{A∩E}}
& {~=~}& {\rm{(A∩B)∪(A∩C)~\color{green}{\text{- - - I}}}}
&{} \\

{\Rightarrow}&{\rm{P(A∩E)}}
& {~=~}& {\rm{P \Bigl((A∩B)∪(A∩C) \Bigr)}}
&{} \\

{\Rightarrow}&{\rm{P(A∩E)}}
& {~=~}& {\rm{P(A∩B)~+~P(A∩C)~-~P \Bigl((A∩B)∩(A∩C) \Bigr)}}
&{} \\

{\Rightarrow}&{\rm{P(A∩E)}}
& {~=~}& {\rm{P(A∩B)~+~P(A∩C)~-~P(A∩B∩C)~\color{green}{\text{- - - II}}}}
&{} \\

\end{array}$

◼ Remarks:
• Line marked as I:
In this line we use the “distribution property of intersection of sets over the union”
• Line marked as II:
Here we use the fact that (A∩B)∩(A∩C) = (A∩B∩C)
5. Now we can make the substitutions:
   ♦ From (3), we have the substitute for P(E)  
   ♦ From (4), we have the substitute for P(A∩E)  
• Making these substitutions in (2), we get:
P(A∪B∪C)
= P(A) + P(B) + P(C) - P(B∩C) - P(A∩B) - P(A∩C) + P(A∩B∩C)

Solved example 16.17
In a relay race there are five teams A, B, C, D and E.
(a) What is the probability that A, B and C finish first, second and third, respectively.
(b) What is the probability that A, B and C are first three to finish (in any order)
(Assume that all finishing orders are equally likely)
Solution:
• Five teams can finish in 5! ways.
• So the number of elements in S = 5! = 120
• We can write: n(S) = 120

Part (i):
1. Let G be the event: A, B and C finish first, second and third respectively.
• There are only two possible outcomes for such a finish. They are:
ABC, D, E and ABC, E, D
• So we can write: n(G) = 2
2. Since all outcomes in S are equally likely, we get:
$\rm{P(G) = \frac{n(G)}{n(S)} = \frac{2}{120} = \frac{1}{60}}$
Part (ii):
1. Let H be the event: A, B and C are the first three to finish in any order.
• A, B and C can arrange among themselves in 3! ways.
   ♦ We have, 3! = 3 × 2 = 6
• For each of those 6 ways, D and E can arrange among themselves in 2! ways.
   ♦ We have, 2! = 2 × 1 = 2 ways.
• So the number of favorable outcomes = 6 × 2 = 12
• We can write: n(H) = 12
2. Since all outcomes in S are equally likely, we get:
$\rm{P(H) = \frac{n(H)}{n(S)} = \frac{12}{120} = \frac{1}{10}}$


Link to a few more solved examples is given below:

Miscellaneous Exercise


In the next section, we will see Appendix A.

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Friday, September 15, 2023

16.8 Solved Examples on Axiomatic Probability

In the previous section, we saw how to calculate the Probability of the event "not A". We saw two solved examples also. In this section, we will see two more solved examples.

Solved example 16.12
Two students Anil and Ashima appeared in an examination. The probability that Anil will qualify the examination is 0.05 and that Ashima will qualify the examination is 0.10. The probability that both will qualify the examination is 0.02. Find the probability that
(a) Both Anil and Ashima will not qualify the examination.
(b) Atleast one of them will not qualify the examination and
(c) Only one of them will qualify the examination.
Solution:
First we will write two basic points. We will number them as 𝛼 and β:
Point 𝛼:
This can be written in 6 steps:
1. Consider the Venn diagram shown in fig.16.2(a) below. It is already familiar to us.

Fig.6.2

2. (Red ∪ Blue) gives set A.
In our present case, A is the event: Anil qualifies in the examination.
3. (Green ∪ Blue) gives set B.
In our present case, B is the event: Ashima qualifies in the examination.
4. Blue is the set (A∩B).
In our present case, (A∩B) is the event: Both Anil and Ashima qualify in the examination.
5. (Red ∪ Blue ∪ Green) gives the set (A∪B).
In our present case, (A∪B) is the event: Anil or Ashima qualifies in the examination.
6. Consider the portion outside (A∪B), but inside the rectangle. That portion gives the set (A∪B)’. It is the portion shown in yellow color in fig.16.2(b) above.
In our present case, (A∪B)’ is the event: Both Anil and Ashima does not qualify in the examination.

Point β:
This can be written in 6 steps:
1. Consider the rectangle S. Imagine that, there are a large number of elements dispersed inside the rectangle. Each of those elements is an outcome.
2. Consider all the outcomes in S. Some of those outcomes are present within (Red ∪ Blue).
• If the outcome of the experiment is from this region, we say that:
Anil has qualified.
• The probability for the outcome to be from this region is given in the question. P(A) = 0.05
3. Consider all the outcomes in S. Some of those outcomes are present within (Green ∪ Blue).
• If the outcome of the experiment is from this region, we say that:
Ashima has qualified.
• The probability for the outcome to be from this region is given in the question. P(B) = 0.1
4. Consider all the outcomes in S. Some of those outcomes are present within Blue.
• If the outcome of the experiment is from this region, we say that:
Both Anil and Ashima have qualified.
• The probability for the outcome to be from this region is given in the question. P(A∩B) = 0.02
5. A and B are not disjoint sets. This can be proved in 3 steps:
(i) If A and B are disjoint sets, (A∩B) = Φ
(ii) Probability of Φ is zero.
(iii) But according to the question, P(A∩B) is not zero. It is 0.02
6. We said that, a large number of outcomes are dispersed within the rectangle S.
• In our present case,
    ♦ we do not know how many such outcomes are there.
    ♦ we do not know the probabilities of each of those outcomes.
• If we knew the number of outcomes and their probabilities, we could calculate P(A), P(B) etc.,
• But as the reader may have already noted, in our present case, we do not need them because, P(A), P(B) and P(A∩B) are already given.  


Now we can answer the questions.
Part (i): Both Anil and Ashima will not qualify.
1. Consider the region (A∪B). It is made up of three regions: red, blue and green.
• If the outcome is from the red region, Anil qualifies. So “Both Anil and Ashima will not qualify” is not satisfied.
• If the outcome is from the blue region, Anil and Ashima qualifies. So “Both Anil and Ashima will not qualify” is not satisfied.
• If the outcome is from the green region, Ashima qualifies. So “Both Anil and Ashima will not qualify” is not satisfied.
• It is clear that, we must discard (A∪B).
2. Consider the region outside (A∪B), but inside the rectangle.
• We know that, such a region is the compliment of set (A∪B). We denote it as (A∪B)’. It is the yellow region of the Venn diagram in fig.16.2(b) above.
• If the outcome is from (A∪B)', we say that:
Both Anil and Ashima will not qualify.
3. The probability for the outcome to be from (A∪B)' is: P(A∪B)'
• So our aim is to find P(A∪B)'
4. It is clear that, (A∪B) and (A∪B)’ are mutually exclusive and exhaustive events.
• We can write:
(A∪B)∪(A∪B)' = S.
• Based on this, we can write the calculations as follows:
$\begin{array}{ll}
{}&{\rm{(A \cup B) \cup (A \cup B)'}}
& {~=~}& {\rm{S}}
&{} \\

{\Rightarrow}&{\rm{P \Bigl((A \cup B) \cup (A \cup B)' \Bigr)}}
& {~=~}& {\rm{P(S)}}
&{} \\

{\Rightarrow}&{\rm{P(A \cup B) + P(A \cup B)'}}
& {~=~}& {\rm{P(S)~\color{green}{\text{- - - I}}}}
&{} \\

{\Rightarrow}&{\rm{P(A) + P(B) - P(A \cap B) + P(A \cup B)'}}
& {~=~}& {\rm{P(S)~\color{green}{\text{- - - II}}}}
&{} \\

{\Rightarrow}&{\rm{0.05 + 0.1 - 0.02 + P(A \cup B)'}}
& {~=~}& {\rm{1}}
&{} \\

{\Rightarrow}&{\rm{0.13 + P(A \cup B)'}}
& {~=~}& {\rm{1}}
&{} \\

{\Rightarrow}&{\rm{P(A \cup B)'}}
& {~=~}& {\rm{1 - 0.13}}
&{} \\

{\Rightarrow}&{\rm{P(A \cup B)'}}
& {~=~}& {\rm{0.87}}
&{} \\

\end{array}$

◼ Remarks:
• Line marked as I:
In this line we use the formula:
P(E∪F) = P(E) + P(F)
Where E and F are disjoint sets.
• Line marked as II:
In this line we use the formula:
P(E∪F) = P(E) + P(F) - P(E∩F)
Where E and F are not disjoint sets.

Part (ii): Atleast one of them will not qualify the examination
1. Consider the blue region.
If the outcome is from this region, it means that both Anil and Ashima qualifies for the examination. So we have to discard this region.
2. Consider the region outside blue but inside the rectangle. This region is (A∩B)’
• This (A∩B)’ is made up of three regions:
(i) Red region (ii) Green region (iii) yellow region.
3. Let us examine each of the three regions.
(i) If the outcome is from the red region, then Anil qualifies but Ashima does not qualify. So “atleast one of them will not qualify” is satisfied.
(ii) If the outcome is from the green region, then Ashima qualifies but Anil does not qualify. So “atleast one of them will not qualify” is satisfied.
(iii) If the outcome is from yellow region, then both do not qualify. So “atleast one of them will not qualify” is satisfied.
4. So (A∩B)’ is our required region.
• The probability for the outcome to be from this region is: P(A∩B)’
5. We have:

$\begin{array}{ll}
{}&{\rm{P(A \cap B)'}}
& {~=~}& {\rm{1 - P(A \cap B)}} &{} \\

{}&{}
& {~=~}& {\rm{1 - 0.02}} &{} \\

{}&{}
& {~=~}& {\rm{0.98}} &{} \\

\end{array}$

Part (iii): Only one of them will qualify the examination.
1. Let us examine each region in fig.16.2 above.
(i) The red region.
If the outcome is from red, then only Anil qualifies. So this region can be considered for our answer.
(ii) The blue region.
If the outcome is from blue, then both qualify. So this region cannot be considered for our answer.
(iii) Green region.
If the outcome is from green, then only Ashima qualifies. So this region can be considered for our answer.
(iv) Yellow region.
If the outcome is from yellow , then neither Anil nor Ashima qualifies. So this region cannot be considered for our answer.
2. Based on the above step, we can write:
The only regions than can be considered are: red and green.
3. We can create a new set: (red ∪ green)
If the outcome is from this union, there are two possibilities:
(i) outcome is from red.
Then only Anil qualifies. So “only one of them will qualify” is satisfied.
(ii) outcome is from green.
Then only Ashima qualifies. So “only one of them will qualify” is satisfied.
4. So (red ∪ green) is our required region.
    ♦ Red is (A-B)
    ♦ Green is (B-A)
• So (A-B)∪(B-A) is our required region.
5. Probability for the outcome to be from this region is: $P \Bigl((A-B) \cup (B-A) \Bigr)$
• (A-B) and (B-A) are disjoint sets. So we can write:
$P \Bigl((A-B) \cup (B-A) \Bigr) = P \Bigl((A-B)\Bigr) + P \Bigl((B-A)\Bigr)$
• So we have to calculate $P \Bigl((A-B)\Bigr) ~\text{and}~ P \Bigl((B-A)\Bigr)$
6. First we will calculate $P \Bigl((A-B)\Bigr)$

$\begin{array}{ll}
{}&{\rm{A}}
& {~=~}& {\rm{(A-B) \cup (A \cap B)~\color{green}{\text{- - - I}}}}
&{} \\

{\Rightarrow}&{\rm{P(A)}}
& {~=~}& {\rm{P \Bigl((A-B) \cup (A \cap B)\Bigr)}}
&{} \\

{\Rightarrow}&{\rm{P(A)}}
& {~=~}& {\rm{P \Bigl((A-B)\Bigr) ~+~ P \Bigl((A \cap B)\Bigr)~\color{green}{\text{- - - II}}}}
&{} \\

{\Rightarrow}&{\rm{0.05}}
& {~=~}& {\rm{P \Bigl((A-B)\Bigr) ~+~ 0.02}}
&{} \\

{\Rightarrow}&{\rm{P \Bigl((A-B)\Bigr)}}
& {~=~}& {\rm{0.05~-~ 0.02}}
&{} \\

{\Rightarrow}&{\rm{P \Bigl((A-B)\Bigr)}}
& {~=~}& {\rm{0.03}}
&{} \\

\end{array}$

◼ Remarks:
• Line marked as I:
Set A is the union of red and blue.
• Line marked as II:
We are able to simply add the individual probabilities because, (A-B) and (A∩B) are disjoint sets.

7. Next we will calculate $P \Bigl((B-A)\Bigr)$

$\begin{array}{ll}
{}&{\rm{B}}
& {~=~}& {\rm{(B-A) \cup (A \cap B)~\color{green}{\text{- - - I}}}}
&{} \\

{\Rightarrow}&{\rm{P(B)}}
& {~=~}& {\rm{P \Bigl((B-A) \cup (A \cap B)\Bigr)}}
&{} \\

{\Rightarrow}&{\rm{P(B)}}
& {~=~}& {\rm{P \Bigl((B-A)\Bigr) ~+~ P \Bigl((A \cap B)\Bigr)~\color{green}{\text{- - - II}}}}
&{} \\

{\Rightarrow}&{\rm{0.1}}
& {~=~}& {\rm{P \Bigl((B-A)\Bigr) ~+~ 0.02}}
&{} \\

{\Rightarrow}&{\rm{P \Bigl((B-A)\Bigr)}}
& {~=~}& {\rm{0.1~-~ 0.02}}
&{} \\

{\Rightarrow}&{\rm{P \Bigl((B-A)\Bigr)}}
& {~=~}& {\rm{0.08}}
&{} \\

\end{array}$

◼ Remarks:
• Line marked as I:
Set B is the union of green and blue.
• Line marked as II:
We are able to simply add the individual probabilities because, (B-A) and (A∩B) are disjoint sets. 

8. Substituting the results from (6) and (7) in (5), we get:
$P \Bigl((A-B) \cup (B-A) \Bigr) = 0.03 + 0.08 = 0.11$


Solved example 16.13
A committee of two persons is selected from two men and two women. What is the probability that the committee will have (a) no man? (b) one man? (c) two men?
Solution:
◼ There are two men (M1 & M2) and two women (W1 & W2)
    ♦ So there is a total of four persons
◼ From that four, two persons can be selected in $\rm{{}^4 C_2}$ ways.
    ♦ So the number of possible outcomes = $\rm{{}^4 C_2}$
    ♦ We can write: n(S) = $\rm{{}^4 C_2}$
    ♦ All the $\rm{{}^4 C_2}$ outcomes are equally likely.
    ♦ Some of those outcomes are: (M1, W1), (W2, M1), etc.,
• Now we can do the calculations:
Part (i):
1. Let A be the event: Getting an outcome with no man.  
2. Since there is to be no man, we must not consider M1 and M2 while making the selections.
• That means, we must consider W1 and W2 only.
• Two women can be selected from two women in $\rm{{}^2 C_2}$ ways.
• So n(A) = $\rm{{}^2 C_2}$
3. Since all outcomes are equally likely, we get:
$\rm{P(A) = \frac{n(A)}{n(S)} = \frac{{}^2 C_2}{{}^4 C_2} = \frac{1}{6}}$

Part (ii):
1. Let B be the event: Getting an outcome with one man.
2. Since there is to be exactly one man, the other person in the committee will be woman.
• One man can be selected from two men in $\rm{{}^2 C_1}$ ways.
• One woman can be selected from two women in $\rm{{}^2 C_1}$ ways.
• Together, they can be selected in $\rm{{}^2 C_1 \times {}^2 C_1}$ ways.
• So n(B) = $\rm{{}^2 C_1 \times {}^2 C_1}$
3. Since all outcomes are equally likely, we get:
$\rm{P(B) = \frac{n(B)}{n(S)} = \frac{{}^2 C_1 \times {}^2 C_1}{{}^4 C_2} = \frac{2 \times 2}{6} = \frac{2}{3}}$

Part (iii):
1. Let C be the event: Getting an outcome with two men.  
2. Since there is to be two men, we must not consider W1 and W2 while making the selections.
• That means, we must consider M1 and M2 only.
• Two men can be selected from two men in $\rm{{}^2 C_2}$ ways.
• So n(C) = $\rm{{}^2 C_2}$
3. Since all outcomes are equally likely, we get:
$\rm{P(C) = \frac{n(C)}{n(S)} = \frac{{}^2 C_2}{{}^4 C_2} = \frac{1}{6}}$


Link to a few more solved examples is given below:

Exercise 16.3


In the next section, we will see some miscellaneous examples.

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