The given sequence is $k, 2k, 3k, \dots, 1000k$. This is an arithmetic progression with $N=1000$ terms.
Since the number of terms ($N=1000$) is even, the median ($M$) is the average of the $\frac{N}{2}^{th}$ and $(\frac{N}{2} + 1)^{th}$ terms.
Median $M = \frac{500k + 501k}{2} = \frac{1001k}{2} = 500.5k$.
The mean deviation (MD) about the median is calculated using the formula:
$ MD = \frac{1}{N} \sum_{i=1}^{N} |x_i - M| $
Here, $x_i = ik$ and $M = 500.5k$. The terms are:
$ |x_i - M| = |ik - 500.5k| = k |i - 500.5| $
The sum of the absolute deviations is:
$ \sum_{i=1}^{1000} |x_i - M| = \sum_{i=1}^{1000} k |i - 500.5| = k \sum_{i=1}^{1000} |i - 500.5| $
We can split the sum:
Sum $= k \left[ \sum_{i=1}^{500} (500.5 - i) + \sum_{i=501}^{1000} (i - 500.5) \right]$
Calculating the sums:
Total sum of absolute deviations $= k [125000 + 125000] = 250000k$.
Mean Deviation $MD = \frac{250000k}{1000} = 250k$.
We are given that the mean deviation about the median is 500.
$ MD = 250k = 500 $
Solving for $k$:
$ k = \frac{500}{250} = 2 $
We need to find $k^2$.
$ k^2 = 2^2 = 4 $
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
If the mean of the data: 7,8,9,7,8,7,$\lambda$,8 is 8, then the variance of this data is :-
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
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