The problem asks us to find the probability $P(X\geq 3)$ for a discrete random variable X, whose probability mass function (PMF) is given by $P(X= x) = k(x + 1)3^{-x}$ for $x = 0, 1, 2, 3\dots$. Here, $k$ is a constant that needs to be determined first.
The sum of probabilities for all possible values of a random variable must equal 1. Therefore, we have:
$ \sum_{x=0}^{\infty} P(X=x) = 1 $
Substituting the given PMF:
$ \sum_{x=0}^{\infty} k(x + 1)3^{-x} = 1 $
We can factor out the constant $k$:
$ k \sum_{x=0}^{\infty} (x + 1)\left(\frac{1}{3}\right)^x = 1 $
The sum $\sum_{x=0}^{\infty} (x + 1)r^x$ is known to be equal to $\frac{1}{(1-r)^2}$ for $|r|<1$. In this case, $r = 1/3$.
So, the sum evaluates to:
$ \sum_{x=0}^{\infty} (x + 1)\left(\frac{1}{3}\right)^x = \frac{1}{\left(1 - \frac{1}{3}\right)^2} = \frac{1}{\left(\frac{2}{3}\right)^2} = \frac{1}{\frac{4}{9}} = \frac{9}{4} $
Now, substitute this back into the equation for $k$:
$ k \left(\frac{9}{4}\right) = 1 $
Solving for $k$:
$ k = \frac{4}{9} $
The PMF is therefore $P(X=x) = \frac{4}{9}(x + 1)3^{-x}$.
We want to find $P(X\geq 3)$. It is often easier to calculate this using the complement rule: $P(X\geq 3) = 1 - P(X < 3)$.
$P(X < 3)$ is the sum of probabilities for $x=0, 1, 2$:
$ P(X < 3) = P(X=0) + P(X=1) + P(X=2) $
Let's calculate each term:
Now, sum these probabilities:
$ P(X < 3) = \frac{4}{9} + \frac{8}{27} + \frac{4}{27} $
To add these fractions, find a common denominator, which is 27:
$ P(X < 3) = \frac{4 \times 3}{9 \times 3} + \frac{8}{27} + \frac{4}{27} = \frac{12}{27} + \frac{8}{27} + \frac{4}{27} = \frac{12 + 8 + 4}{27} = \frac{24}{27} $
Finally, calculate $P(X\geq 3)$:
$ P(X\geq 3) = 1 - P(X < 3) = 1 - \frac{24}{27} = \frac{27 - 24}{27} = \frac{3}{27} $
Simplify the fraction:
$ P(X\geq 3) = \frac{1}{9} $
If the mean and median of the data
| x | 0-10 | 10-20 | 20-30 | 30-40 | 40-50 | |
| f | 3 | 6 | 2 | x | y | $\Sigma f = 20$ |
are equal, then $xy^2$ is equal to
Consider the following frequency distribution :
| Class | 0 - 6 | 6 - 12 | 12 - 18 | 18 - 24 | 24 - 30 |
| Frequency | a | b | 12 | 9 | 5 |
If mean = $\frac{309}{22}$ and median=$14$, then the value $(a - b)^2$ is equal to ________.
The sum $1+3+11+25+45+71+ ...$ upto 20 terms, is equal to
, $\alpha, \beta \in N$, then $(\alpha + \beta)^2$ is equal to
| X | $4\text{k}$ | $\frac{30}{7}\text{k}$ | $\frac{32}{7}\text{k}$ | $\frac{34}{7}\text{k}$ | $\frac{36}{7}\text{k}$ | $\frac{38}{7}\text{k}$ | $\frac{40}{7}\text{k}$ | $6\text{k}$ |
| P(X) | $\frac{2}{15}$ | $\frac{1}{15}$ | $\frac{2}{15}$ | $\frac{1}{5}$ | $\frac{1}{15}$ | $\frac{2}{15}$ | $\frac{1}{5}$ | $\frac{1}{15}$ |
If the mean and median of the data
| x | 0-10 | 10-20 | 20-30 | 30-40 | 40-50 | |
| f | 3 | 6 | 2 | x | y | $\Sigma f = 20$ |
are equal, then $xy^2$ is equal to
Consider the following frequency distribution :
| Class | 0 - 6 | 6 - 12 | 12 - 18 | 18 - 24 | 24 - 30 |
| Frequency | a | b | 12 | 9 | 5 |
If mean = $\frac{309}{22}$ and median=$14$, then the value $(a - b)^2$ is equal to ________.
The sum $1+3+11+25+45+71+ ...$ upto 20 terms, is equal to