Answer:
a . 1/13
Step-by-step explanation:
For the given probability mass function of X, the mean is 3.5 and the standard deviation is 1.708.
- A discrete random variable X's probability mass function (PMF) is a function over its sample space that estimates the likelihood that X will have a given value. f(x)=P[X=x].
- The total of all potential values for a random variable X, weighted by their relative probabilities, is known as the mean (or expected value E[X]) of that variable.
- Mean(μ) = 1(1/6) + 2(1/6) + 3(1/6) + 4(1/6) + 5(1/6) + 6(1/6).
- Mean(μ) = (1+2+3+4+5+6)/6
- Mean(μ) = 21/6
- Mean(μ) = 3.5
- The square root of the variance of a random variable, sample, statistical population, data collection, or probability distribution represents its standard deviation. It is denoted by 'σ'.
- A random variable's variance (or Var[X]) is a measurement of the range of potential values. It is, by definition, the squared expectation of the distance between X and μ. It is denoted by 'σ²'.
- σ² = E[X²]−μ²
- σ² = [1²(1/6) + 2²(1/6) + 3²(1/6) + 4²(1/6) + 5²(1/6) + 6²(1/6)] - (3.5)²
- σ² = [(1² + 2²+ 3² + 4²+ 5²+ 6²)/6] - (3.5)²
- σ² = [(1 + 4 + 9 + 16 + 25 + 36)/6] - (3.5)²
- σ² = (91/6) - (3.5)²
- σ² = 15.167-12.25
- σ² = 2.917
- σ = √2.917
- Standard deviation (σ) = 1.708
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Answer:
350
Step-by-step explanation:
you just have to subtract ibthink
The initial statement is: QS = SU (1)
QR = TU (2)
We have to probe that: RS = ST
Take the expression (1): QS = SU
We multiply both sides by R (QS)R = (SU)R
But (QS)R = S(QR) Then: S(QR) = (SU)R (3)
From the expression (2): QR = TU. Then, substituting it in to expression (3):
S(TU) = (SU)R (4)
But S(TU) = (ST)U and (SU)R = (RS)U
Then, the expression (4) can be re-written as:
(ST)U = (RS)U
Eliminating U from both sides you have: (ST) = (RS) The proof is done.
(-2)+(-2)+(-2)+(-2)
=-2-2-2-2
= -8
