Related Formula
Mean of N$N$ observations:
x = (Σ xᵢ)/(N)$$\bar{x} = \frac{\sum x_i}{N}$$
Variance of N$N$ observations:
σ² = (Σ xᵢ²)/(N) - ( x)²$$\sigma^2 = \frac{\sum x_i^2}{N} - (\bar{x})^2$$
Core Logic
Given mean is 5$5$ for 5$5$ observations:
(1 + 3 + a + 7 + b)/(5) = 5 a + b + 11 = 25 a + b = 14 --- (1)$$\frac{1 + 3 + a + 7 + b}{5} = 5 \implies a + b + 11 = 25 \implies a + b = 14 \quad \text{--- (1)}$$
Given variance is 10$10$:
(1² + 3² + a² + 7² + b²)/(5) - 5² = 10 (59 + a² + b²)/(5) = 35$$\frac{1^2 + 3^2 + a^2 + 7^2 + b^2}{5} - 5^2 = 10 \implies \frac{59 + a^2 + b^2}{5} = 35$$
a² + b² = 175 - 59 = 116 --- (2)$$a^2 + b^2 = 175 - 59 = 116 \quad \text{--- (2)}$$
Step 1: Finding a$a$ and b$b$
Using standard algebraic identity (a+b)² = a² + b² + 2ab$(a+b)^2 = a^2 + b^2 + 2ab$:
14² = 116 + 2ab 196 = 116 + 2ab ab = 40$$14^2 = 116 + 2ab \implies 196 = 116 + 2ab \implies ab = 40$$
Solving a+b=14$a+b=14$ and ab=40$ab=40$:
a(14-a) = 40 a² - 14a + 40 = 0 (a-10)(a-4) = 0$$a(14-a) = 40 \implies a^2 - 14a + 40 = 0 \implies (a-10)(a-4) = 0$$
Since a > b$a > b$, we obtain a = 10$a = 10$ and b = 4$b = 4$.
Step 2: Constructing new set and finding variance
The original set is x₁ = 1, x₂ = 3, x₃ = 10, x₄ = 7, x₅ = 4$x_1 = 1, x_2 = 3, x_3 = 10, x_4 = 7, x_5 = 4$.
We construct the new set yₙ = n + xₙ$y_n = n + x_n$:
- y₁ = 1 + 1 = 2$y_1 = 1 + 1 = 2$
- y₂ = 2 + 3 = 5$y_2 = 2 + 3 = 5$
- y₃ = 3 + 10 = 13$y_3 = 3 + 10 = 13$
- y₄ = 4 + 7 = 11$y_4 = 4 + 7 = 11$
- y₅ = 5 + 4 = 9$y_5 = 5 + 4 = 9$
Mean of new set:
y = (2 + 5 + 13 + 11 + 9)/(5) = (40)/(5) = 8$$\bar{y} = \frac{2 + 5 + 13 + 11 + 9}{5} = \frac{40}{5} = 8$$
Variance of new set:
σnew² = (2² + 5² + 13² + 11² + 9²)/(5) - 8²$$\sigma_{new}^2 = \frac{2^2 + 5^2 + 13^2 + 11^2 + 9^2}{5} - 8^2$$
σnew² = (4 + 25 + 169 + 121 + 81)/(5) - 64 = (400)/(5) - 64 = 80 - 64 = 16$$\sigma_{new}^2 = \frac{4 + 25 + 169 + 121 + 81}{5} - 64 = \frac{400}{5} - 64 = 80 - 64 = 16$$
Pattern Recognition
Note that adding a changing factor like +n$+n$ is different from adding a constant C$C$ to each observation (which leaves variance unchanged). In this case, calculate individual xₙ$x_n$ variables directly first before applying transformations.
Chapter Mix
Class 11 Mathematics: Statistics and Probability