Actual mean: \[ \mu = \frac{100(40) - 50 + 40}{100} \] \[ \mu = 40 - \frac{1}{10} = 39.9 \] Incorrect variance: \[ (5.1)^2 = \frac{\sum x_i^2}{100} - (\bar{x})^2 \] \[ \sum x_i^2 = 100 \times (40^2) + 100 \times (5.1)^2 \] \[ \sum x_i^2 = 16 \times 10^4 + (5.1)^2 \times 100 = 162601 \] \[ \sigma^2 = \frac{\sum x_i^2 - 50^2 + 40^2}{100} - (\mu)^2 \] \[ \sigma^2 = 1617.01 - (39.9)^2 = 25 \] \[ \sigma = 5 \] \[ 10(\mu + \sigma) = 10(39.9 + 5) \] \[ 10 \times 44.9 = 449 \] \[ \boxed{10(\mu + \sigma) = 449} \]
If the mean and the variance of 6, 4, a, 8, b, 12, 10, 13 are 9 and 9.25 respectively, then \(a + b + ab\) is equal to:
For \( \alpha, \beta, \gamma \in \mathbb{R} \), if \[ \lim_{x \to 0} \frac{x^2 \sin(\alpha x) + (\gamma - 1)e^{x^2}}{\sin(2x - \beta x)} = 3, \] then \( \beta + \gamma - \alpha \) is equal to: