If the probability that the random variable \( X \) takes values \( x \) is given by \( P(X = x) = k(x + 1) 3^{-x}, x = 0, 1, 2, \dots \), where \( k \) is a constant, then \( P(X \geq 2) \) is equal to:
For probability distributions, ensure the sum of all probabilities equals 1. Use geometric series formulas to simplify summations efficiently.
\(\frac{20}{27}\)
\(\frac{7}{27}\)
The total probability is:
\[ \sum_{x=0}^\infty P(X = x) = 1. \]
Substitute \( P(X = x) = k(x + 1) 3^{-x} \):
\[ k \sum_{x=0}^\infty (x + 1) 3^{-x} = 1. \]
Let:
\[ S = \sum_{x=0}^\infty (x + 1) 3^{-x}. \]
Split \( S \) into two components:
\[ S = \sum_{x=0}^\infty 3^{-x} + \sum_{x=1}^\infty x \cdot 3^{-x}. \]
1. For the first term:
The sum of a geometric series is:
\[ \sum_{x=0}^\infty 3^{-x} = \frac{1}{1 - \frac{1}{3}} = \frac{3}{2}. \]
2. For the second term:
Using the formula for a weighted geometric series:
\[ \sum_{x=1}^\infty x \cdot 3^{-x} = \frac{\frac{1}{3}}{\left(1 - \frac{1}{3}\right)^2} = \frac{\frac{1}{3}}{\left(\frac{2}{3}\right)^2} = \frac{3}{4}. \]
Thus:
\[ S = \frac{3}{2} + \frac{3}{4} = \frac{9}{4}. \]
Equating to 1:
\[ k \cdot \frac{9}{4} = 1 \implies k = \frac{4}{9}. \]
Finding \( P(X \geq 2) \):
\[ P(X \geq 2) = 1 - P(X = 0) - P(X = 1). \]
\[ P(X = 0) = \frac{4}{9} \cdot (0 + 1) \cdot 3^0 = \frac{4}{9}. \]
\[ P(X = 1) = \frac{4}{9} \cdot (1 + 1) \cdot 3^{-1} = \frac{4}{9} \cdot 2 \cdot \frac{1}{3} = \frac{8}{27}. \]
\[ P(X \geq 2) = 1 - \frac{4}{9} - \frac{8}{27} = \frac{27}{27} - \frac{12}{27} - \frac{8}{27} = \frac{7}{27}. \]
If probability of happening of an event is 57%, then probability of non-happening of the event is
In the following \(p\text{–}V\) diagram, the equation of state along the curved path is given by \[ (V-2)^2 = 4ap, \] where \(a\) is a constant. The total work done in the closed path is: 
Let \( ABC \) be a triangle. Consider four points \( p_1, p_2, p_3, p_4 \) on the side \( AB \), five points \( p_5, p_6, p_7, p_8, p_9 \) on the side \( BC \), and four points \( p_{10}, p_{11}, p_{12}, p_{13} \) on the side \( AC \). None of these points is a vertex of the triangle \( ABC \). Then the total number of pentagons that can be formed by taking all the vertices from the points \( p_1, p_2, \ldots, p_{13} \) is ___________.
Conditional Probability is defined as the occurrence of any event which determines the probability of happening of the other events. Let us imagine a situation, a company allows two days’ holidays in a week apart from Sunday. If Saturday is considered as a holiday, then what would be the probability of Tuesday being considered a holiday as well? To find this out, we use the term Conditional Probability.
P(S | B) = P(B | B) = 1.
Proof of the same: P(S | B) = P(S ∩ B) ⁄ P(B) = P(B) ⁄ P(B) = 1.
[S ∩ B indicates the outcomes common in S and B equals the outcomes in B].
P(B | A), P(A) >0 or, P(A ∩ B) = P(B).P(A | B), P(B) > 0.
This theorem is named as the Multiplication Theorem of Probability.
Proof of the same: As we all know that P(B | A) = P(B ∩ A) / P(A), P(A) ≠ 0.
We can also say that P(B|A) = P(A ∩ B) ⁄ P(A) (as A ∩ B = B ∩ A).
So, P(A ∩ B) = P(A). P(B | A).
Similarly, P(A ∩ B) = P(B). P(A | B).
The interesting information regarding the Multiplication Theorem is that it can further be extended to more than two events and not just limited to the two events. So, one can also use this theorem to find out the conditional probability in terms of A, B, or C.
Read More: Types of Sets
Sometimes students get confused between Conditional Probability and Joint Probability. It is essential to know the differences between the two.