1. Найдем математическое ожидание M(X):
$$M(X) = \sum_{i=1}^{n} x_i p_i$$ $$M(X) = (-1 \times 0.1) + (-2 \times 0.3) + (-3 \times 0.1) + (-10 \times 0.005) + (-12 \times 0.1) + (-20 \times 0.005) + (-30 \times 0.3) + (-40 \times 0.09)$$ $$M(X) = -0.1 - 0.6 - 0.3 - 0.05 - 1.2 - 0.1 - 9 - 3.6 = -14.95$$2. Найдем дисперсию D(X):
$$D(X) = M(X^2) - [M(X)]^2$$ Сначала найдем M(X^2): $$M(X^2) = \sum_{i=1}^{n} x_i^2 p_i$$ $$M(X^2) = ((-1)^2 \times 0.1) + ((-2)^2 \times 0.3) + ((-3)^2 \times 0.1) + ((-10)^2 \times 0.005) + ((-12)^2 \times 0.1) + ((-20)^2 \times 0.005) + ((-30)^2 \times 0.3) + ((-40)^2 \times 0.09)$$ $$M(X^2) = (1 \times 0.1) + (4 \times 0.3) + (9 \times 0.1) + (100 \times 0.005) + (144 \times 0.1) + (400 \times 0.005) + (900 \times 0.3) + (1600 \times 0.09)$$ $$M(X^2) = 0.1 + 1.2 + 0.9 + 0.5 + 14.4 + 2 + 270 + 144 = 433.1$$ Теперь найдем D(X): $$D(X) = 433.1 - (-14.95)^2$$ $$D(X) = 433.1 - 223.5025 = 209.5975$$3. Найдем среднее квадратичное отклонение σ(X):
$$\sigma(X) = \sqrt{D(X)}$$ $$\sigma(X) = \sqrt{209.5975} \approx 14.4775$$Ответ:
$$M(X) = -14.95$$ $$D(X) = 209.5975$$ $$\sigma(X) \approx 14.4775$$