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For a discrete probability distribution, the sum of all probabilities must equal 1.

Mathematics

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3 parts
a

130\frac{1}{30}

b

4915\frac{49}{15}

c

434225\frac{434}{225}

Step-by-step solution

8 steps

Part a· 3 steps

Calculate the constant C

  1. For a discrete probability distribution, the sum of all probabilities must equal 1.

    ∑xP(X=x)=1\sum_{x} P(X=x) = 1
  2. List the probabilities for each value of xx.

    For x=1,2,3x=1,2,3: P(X=x)=Cx2P(X=x) = Cx^2
    P(X=1)=C(1)2=CP(X=1) = C(1)^2 = C
    P(X=2)=C(2)2=4CP(X=2) = C(2)^2 = 4C
    P(X=3)=C(3)2=9CP(X=3) = C(3)^2 = 9C

    For x=4,5,6x=4,5,6: P(X=x)=C(7−x)2P(X=x) = C(7-x)^2
    P(X=4)=C(7−4)2=C(3)2=9CP(X=4) = C(7-4)^2 = C(3)^2 = 9C
    P(X=5)=C(7−5)2=C(2)2=4CP(X=5) = C(7-5)^2 = C(2)^2 = 4C
    P(X=6)=C(7−6)2=C(1)2=CP(X=6) = C(7-6)^2 = C(1)^2 = C

  3. Sum all probabilities and set equal to 1 to solve for CC.

    C+4C+9C+9C+4C+C=1C + 4C + 9C + 9C + 4C + C = 1 30C=130C = 1 C=130C = \frac{1}{30}

    The constant C is 130\boxed{\frac{1}{30}}.

Part b

4915\frac{49}{15}

Calculate the mean of X

  1. The mean E(X)E(X) is calculated using the formula E(X)=∑xx⋅P(X=x)E(X) = \sum_{x} x \cdot P(X=x).

    Substitute C=130C = \frac{1}{30} into the probabilities:
    P(X=1)=130P(X=1) = \frac{1}{30}
    P(X=2)=430P(X=2) = \frac{4}{30}
    P(X=3)=930P(X=3) = \frac{9}{30}
    P(X=4)=930P(X=4) = \frac{9}{30}
    P(X=5)=430P(X=5) = \frac{4}{30}
    P(X=6)=130P(X=6) = \frac{1}{30}

  2. Calculate E(X)E(X).

    E(X)=(1)(130)+(2)(430)+(3)(930)+(4)(930)+(5)(430)+(6)(130)E(X) = (1)\left(\frac{1}{30}\right) + (2)\left(\frac{4}{30}\right) + (3)\left(\frac{9}{30}\right) + (4)\left(\frac{9}{30}\right) + (5)\left(\frac{4}{30}\right) + (6)\left(\frac{1}{30}\right) E(X)=130(1+8+27+36+20+6)E(X) = \frac{1}{30}(1 + 8 + 27 + 36 + 20 + 6) E(X)=130(98)E(X) = \frac{1}{30}(98) E(X)=9830=4915E(X) = \frac{98}{30} = \frac{49}{15}

    The mean of X is 4915\boxed{\frac{49}{15}}.

Part c

434225\frac{434}{225}

Calculate the variance of X

  1. The variance Var(X)Var(X) is calculated using the formula Var(X)=E(X2)−(E(X))2Var(X) = E(X^2) - (E(X))^2.

    First, calculate E(X2)E(X^2).

    E(X2)=∑xx2⋅P(X=x)E(X^2) = \sum_{x} x^2 \cdot P(X=x) E(X2)=(12)(130)+(22)(430)+(32)(930)+(42)(930)+(52)(430)+(62)(130)E(X^2) = (1^2)\left(\frac{1}{30}\right) + (2^2)\left(\frac{4}{30}\right) + (3^2)\left(\frac{9}{30}\right) + (4^2)\left(\frac{9}{30}\right) + (5^2)\left(\frac{4}{30}\right) + (6^2)\left(\frac{1}{30}\right) E(X2)=130(1⋅1+4⋅4+9⋅9+16⋅9+25⋅4+36⋅1)E(X^2) = \frac{1}{30}(1 \cdot 1 + 4 \cdot 4 + 9 \cdot 9 + 16 \cdot 9 + 25 \cdot 4 + 36 \cdot 1) E(X2)=130(1+16+81+144+100+36)E(X^2) = \frac{1}{30}(1 + 16 + 81 + 144 + 100 + 36) E(X2)=130(378)E(X^2) = \frac{1}{30}(378) E(X2)=37830=635E(X^2) = \frac{378}{30} = \frac{63}{5}
  2. Calculate Var(X)Var(X) using E(X2)E(X^2) and E(X)=4915E(X) = \frac{49}{15}.

    Var(X)=635−(4915)2Var(X) = \frac{63}{5} - \left(\frac{49}{15}\right)^2 Var(X)=635−2401225Var(X) = \frac{63}{5} - \frac{2401}{225} Var(X)=63×455×45−2401225Var(X) = \frac{63 \times 45}{5 \times 45} - \frac{2401}{225} Var(X)=2835225−2401225Var(X) = \frac{2835}{225} - \frac{2401}{225} Var(X)=2835−2401225Var(X) = \frac{2835 - 2401}{225} Var(X)=434225Var(X) = \frac{434}{225}

    The variance of X is 434225\boxed{\frac{434}{225}}.

Part d· 1 step

Calculate the mean and variance of Y, where Y=3X−1Y = 3X - 1

  1. Use the properties of expectation for a linear transformation

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