Given, Mean \( \bar{x} = \frac{\sum x_i}{n} = \frac{1 + 3 + a + 7 + b}{5} = 5 \)
\[
11 + a + b = 25
\]
\[
a + b = 14
\]
Given, Variance \( \sigma^2 = \frac{\sum x_i^2}{n} - \left( \bar{x} \right)^2 = 10 \)
\[
\frac{1^2 + 3^2 + a^2 + 7^2 + b^2}{5} - (5)^2 = 10
\]
\[
\frac{1 + 9 + a^2 + 49 + b^2}{5} - 25 = 10
\]
\[
59 + a^2 + b^2 = 175
\]
\[
a^2 + b^2 = 116
\]
We are given:
\[
a + b = 14 \quad \text{and} \quad a^2 + b^2 = 116
\]
Using the identity:
\[
(a + b)^2 = a^2 + b^2 + 2ab
\]
Substitute the known values:
\[
14^2 = 116 + 2ab
\]
\[
196 = 116 + 2ab
\]
\[
2ab = 80 \Rightarrow ab = 40
\]
Now solve the system:
\[
a + b = 14, \quad ab = 40
\]
Form the quadratic:
\[
t^2 - (a + b)t + ab = 0
\]
\[
t^2 - 14t + 40 = 0
\]
\[
(t - 10)(t - 4) = 0
\]
So,
\[
t = 10 \quad \text{or} \quad t = 4
\]
Given \( a>b \), we have:
\[
a = 10, \quad b = 4
\]
The observations \( x_i \) are:
\[
1, 3, 10, 7, 4
\]
The new observations \( n + x_n \) for \( n = 1 \) to \( 5 \) are:
\[
1 + x_1 = 2, \quad 2 + x_2 = 5, \quad 3 + x_3 = 13, \quad 4 + x_4 = 11, \quad 5 + x_5 = 9
\]
New set:
\[
2, 5, 13, 11, 9
\]
Mean:
\[
\frac{2 + 5 + 13 + 11 + 9}{5} = \frac{40}{5} = 8
\]
Variance:
\[
\frac{2^2 + 5^2 + 13^2 + 11^2 + 9^2}{5} - (8)^2
\]
\[
= \frac{4 + 25 + 169 + 121 + 81}{5} - 64
\]
\[
= \frac{400}{5} - 64 = 80 - 64 = 16
\]