$x_i$ 1 2 3 ... $n$ $f_i$ 1 $2^{-1}$ $2^{-2}$ ... $2^{-(n-1)}$
The question provides a discrete distribution with values $x_i$ and corresponding frequencies $f_i$. We need to calculate the mean ($\bar{x}$) of this distribution.
The data given is:
We can rewrite the frequencies as:
$ f_i = \frac{1}{2^{i-1}} $
The mean ($\bar{x}$) of a discrete distribution is defined as the sum of the products of each value and its corresponding frequency:
$ \bar{x} = \sum_{i=1}^{n} x_i f_i $
Substitute the given $x_i$ and $f_i$ values into the formula:
$ \bar{x} = \sum_{i=1}^{n} i \cdot \frac{1}{2^{i-1}} $
Let's write out the terms of the sum:
$ \bar{x} = \left( 1 \cdot \frac{1}{2^{1-1}} \right) + \left( 2 \cdot \frac{1}{2^{2-1}} \right) + \left( 3 \cdot \frac{1}{2^{3-1}} \right) + \dots + \left( n \cdot \frac{1}{2^{n-1}} \right) $
$ \bar{x} = \left( 1 \cdot \frac{1}{2^0} \right) + \left( 2 \cdot \frac{1}{2^1} \right) + \left( 3 \cdot \frac{1}{2^2} \right) + \dots + \left( n \cdot \frac{1}{2^{n-1}} \right) $
$ \bar{x} = 1 + \frac{2}{2} + \frac{3}{4} + \dots + \frac{n}{2^{n-1}} $
The sum we need to calculate is an arithmetico-geometric series. Let $S_n$ represent this sum:
$ S_n = 1 + \frac{2}{2} + \frac{3}{4} + \dots + \frac{n}{2^{n-1}} $
Let $r = \frac{1}{2}$. Then the series can be written as:
$ S_n = \sum_{i=1}^{n} i \cdot r^{i-1} = 1 + 2r + 3r^2 + \dots + nr^{n-1} $
To find the sum $S_n$, we use a standard method. Multiply the entire series by $r$:
$ rS_n = r + 2r^2 + 3r^3 + \dots + (n-1)r^{n-1} + nr^n $
Now, subtract $rS_n$ from $S_n$:
$ S_n - rS_n = (1 + 2r + 3r^2 + \dots + nr^{n-1}) - (r + 2r^2 + \dots + nr^n) $
Group the terms:
$ S_n(1-r) = 1 + (2r-r) + (3r^2-2r^2) + \dots + (nr^{n-1} - (n-1)r^{n-1}) - nr^n $
$ S_n(1-r) = 1 + r + r^2 + \dots + r^{n-1} - nr^n $
The sum $1 + r + r^2 + \dots + r^{n-1}$ is a finite geometric series. Its sum is $\frac{1 - r^n}{1 - r}$.
$ S_n(1-r) = \frac{1 - r^n}{1 - r} - nr^n $
Now, substitute $r = \frac{1}{2}$. This means $1-r = \frac{1}{2}$:
$ S_n \left( \frac{1}{2} \right) = \frac{1 - \left(\frac{1}{2}\right)^n}{\frac{1}{2}} - n \left(\frac{1}{2}\right)^n $
Simplify the equation:
$ \frac{S_n}{2} = 2 \left( 1 - \frac{1}{2^n} \right) - \frac{n}{2^n} $
$ \frac{S_n}{2} = 2 - \frac{2}{2^n} - \frac{n}{2^n} $
$ \frac{S_n}{2} = 2 - \frac{n+2}{2^n} $
To find $S_n$, multiply both sides by 2:
$ S_n = 2 \left( 2 - \frac{n+2}{2^n} \right) $
$ S_n = 4 - \frac{2(n+2)}{2^n} $
Simplify the fraction:
$ S_n = 4 - \frac{n+2}{2^{n-1}} $
To express this as a single fraction with the denominator $2^{n-1}$:
$ S_n = \frac{4 \cdot 2^{n-1}}{2^{n-1}} - \frac{n+2}{2^{n-1}} $
$ S_n = \frac{2^2 \cdot 2^{n-1} - (n+2)}{2^{n-1}} $
$ S_n = \frac{2^{n+1} - n - 2}{2^{n-1}} $
The calculated mean ($\bar{x}$) of the distribution is:
$ \bar{x} = \frac{2^{n+1} - n - 2}{2^{n-1}} $
What is the median height of the class?
What is the total number of students whose height is less than or equal to 165 cm?
The height which occurs most frequently in the class is
| LIST-I | LIST-II | |
| A. Sampling error | I. | Values that describe the characteristics of a population |
| B. Parameters | II. | The standard deviation of the sampling distribution |
| C. Sampling fraction | III. | Variation among sample statistics due to change |
| D. Standard error | IV. | Proportion of the population contained in a sample |
Given below are two statements one is labelled as Assertion (A) and the other is labelled as
Reason (R).
Assertion (A): Additive model considers the total of various components resulting in the given
values of the over all time series and it is stated as:
$Y=T+C+S+I$
Reason (R): Multiplicative model assumes that the various components interact in a
multiplicative manner to produce the given values of the over all time series and
can be stated as $Y=T \times C \times S \times I$
In the light of the above statements, choose the most appropriate answer from the options given
below:
Match List - I with List - II.
| List - I | List - II |
| A. Sample proportion P = x/n | I. $\frac{\sigma}{\sqrt{n}}$ |
| B. Sample variance $S_1^2 = \frac{1}{n-1} \sum_{i=1}^{n}(xi-x̄)^2$ | II. $\sigma^2 \sqrt{\frac{2}{n}}$ |
| C. Sample variance $S^2 = \frac{1}{n} \sum_{i=1}^{n}(xi-x̄)^2$ | III. $\sigma^2 \sqrt{\frac{2}{(n-1)}}$ |
| D. Sample mean $\bar{x} = \frac{1}{n} \sum_{i=1}^{n}xi$ | IV. $\sqrt{\frac{\pi(1-\pi)}{n}}$ |
Choose the correct answer from the options given below :