Calculate mean, variance and standard deviation for the following distribution.
Classes | $30-40$ | $40-50$ | $50-60$ | $60-70$ | $70-80$ | $80-90$ | $90-100$ |
${f_i}$ | $3$ | $7$ | $12$ | $15$ | $8$ | $3$ | $2$ |
Let the assumed mean $A =65 .$ Here $h=10$
We obtain the following Table from the given data :
Class |
Frequency ${f_i}$ |
Mid-point ${x_i}$ |
${y_i} = \frac{{{x_i} - 65}}{{10}}$ | ${y_i}^2$ | ${f_i}{y_i}$ | ${f_i}{y_i}^2$ |
$30-40$ | $3$ | $35$ | $-3$ | $9$ | $-9$ | $27$ |
$40-50$ | $7$ | $45$ | $-2$ | $4$ | $-14$ | $28$ |
$50-60$ | $12$ | $55$ | $-1$ | $1$ | $-12$ | $12$ |
$60-70$ | $15$ | $65$ | $0$ | $0$ | $0$ | $0$ |
$70-80$ | $8$ | $75$ | $1$ | $1$ | $8$ | $8$ |
$80-90$ | $3$ | $85$ | $2$ | $4$ | $6$ | $12$ |
$90-100$ | $2$ | $95$ | $3$ | $9$ | $6$ | $18$ |
$N=50$ | $-15$ | $105$ |
Therefore $\bar x = A + \frac{{\sum {{f_i}{y_i}} }}{{50}} \times h = 65 - \frac{{15}}{{50}} \times 10 = 62$
Variance ${\sigma ^2} = \frac{{{h^2}}}{{{N^2}}}\left[ {N{{\sum {{f_i}{y_i}} }^2} - {{\left( {\sum {{f_i}{y_i}} } \right)}^2}} \right]$
$=\frac{(10)^{2}}{(50)^{2}}\left[50 \times 105-(-15)^{2}\right]$
$=\frac{1}{25}[5250-225]=201$
and standard deviation $(\sigma)=\sqrt{201}=14.18$
The mean of two samples of size $200$ and $300$ were found to be $25, 10$ respectively their $S.D.$ is $3$ and $4$ respectively then variance of combined sample of size $500$ is :-
The varience of data $1001, 1003, 1006, 1007, 1009, 1010$ is -
For the frequency distribution :
Variate $( x )$ | $x _{1}$ | $x _{1}$ | $x _{3} \ldots \ldots x _{15}$ |
Frequency $(f)$ | $f _{1}$ | $f _{1}$ | $f _{3} \ldots f _{15}$ |
where $0< x _{1}< x _{2}< x _{3}<\ldots .< x _{15}=10$ and
$\sum \limits_{i=1}^{15} f_{i}>0,$ the standard deviation cannot be
Mean of $5$ observations is $7.$ If four of these observations are $6, 7, 8, 10$ and one is missing then the variance of all the five observations is
Let the mean and variance of $8$ numbers $x , y , 10$, $12,6,12,4,8$, be $9$ and $9.25$ respectively. If $x > y$, then $3 x-2 y$ is equal to $...........$.