This solution details the calculation of $\alpha + \beta$ based on changes in the mean and variance of a dataset after an observation is replaced.
We are given a dataset with 10 observations ($n=10$).
The sum of the original 10 observations ($\sum x_i$) is calculated using the formula $\sum x_i = n \times \bar{x}$.
Calculation: $\sum x_i = 10 \times 10 = 100$.
The variance formula is $\sigma^2 = \frac{\sum x_i^2}{n} - (\bar{x})^2$. We use this to find the sum of squares ($\sum x_i^2$).
Calculation: $2 = \frac{\sum x_i^2}{10} - (10)^2$ $2 = \frac{\sum x_i^2}{10} - 100$ $102 = \frac{\sum x_i^2}{10}$ $\sum x_i^2 = 1020$
One observation, $\alpha$, is replaced by $\beta$. The number of observations remains $n=10$.
The new sum of observations ($\sum x_i'$) is $\sum x_i' = (\sum x_i - \alpha) + \beta$.
Using the new mean, $\sum x_i' = n \times \bar{x}' = 10 \times 10.1 = 101$.
Equating the two expressions for the new sum:
$101 = (100 - \alpha) + \beta$ $101 = 100 - \alpha + \beta$
This gives us our first equation:
$\beta - \alpha = 1$ (Equation 1)
The new sum of squares ($\sum x_i'^2$) is $\sum x_i'^2 = (\sum x_i^2 - \alpha^2) + \beta^2$.
Using the new variance formula: $\sigma'^2 = \frac{\sum x_i'^2}{n} - (\bar{x}')^2$.
Substituting the known values:
$1.99 = \frac{1020 - \alpha^2 + \beta^2}{10} - (10.1)^2$ $1.99 = \frac{1020 - \alpha^2 + \beta^2}{10} - 102.01$ $1.99 + 102.01 = \frac{1020 - \alpha^2 + \beta^2}{10}$ $104 = \frac{1020 - \alpha^2 + \beta^2}{10}$ $1040 = 1020 - \alpha^2 + \beta^2$
Rearranging gives our second equation:
$\beta^2 - \alpha^2 = 1040 - 1020$
$\beta^2 - \alpha^2 = 20$ (Equation 2)
We have two equations:
Factorizing Equation 2 using the difference of squares formula ($a^2 - b^2 = (a-b)(a+b)$):
$(\beta - \alpha)(\beta + \alpha) = 20$.
Substitute the value of $(\beta - \alpha)$ from Equation 1 into the factorized Equation 2:
$(1)(\beta + \alpha) = 20$.
Therefore:
$\alpha + \beta = 20$.
The value of $\alpha + \beta$ is 20.
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
If the mean of the data: 7,8,9,7,8,7,$\lambda$,8 is 8, then the variance of this data is :-
Four dice are thrown simultaneously and the numbers shown on these dice are recorded in $2\times2$ matrices. The probability that such formed matrices have all different entries and are non-singular, is :
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 ________.
| 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) | $\frac{2}{15}$ | $\frac{1}{15}$ | $\frac{2}{15}$ | $\frac{1}{5}$ | $\frac{1}{15}$ | $\frac{2}{15}$ | $\frac{1}{5}$ | $\frac{1}{15}$ |
Let the mean and variance of 8 numbers $-10, -7, -1, x, y, 9, 2, 16$ be $\frac{7}{2}$ and $\frac{293}{4}$, respectively.
Then the mean of 4 numbers $x, y, x + y + 1, |x - y|$ 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
If the mean of the data: 7,8,9,7,8,7,$\lambda$,8 is 8, then the variance of this data is :-
Four dice are thrown simultaneously and the numbers shown on these dice are recorded in $2\times2$ matrices. The probability that such formed matrices have all different entries and are non-singular, is :