Hello, can someone please help me asap! thanks
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Answer:
Significance of the mean of a probability distribution.
Step-by-step explanation:
- The mean of a probability distribution is the arithmetic average value of a random variable having that distribution.
- For a discrete probability distribution, the mean is given by,
, where P(x) is the probabiliy mass function.
- For a continuous probability distribution, the mean s given by,
, where f(x) is the probability density function.
- Mean is a measure of central location of a random variable.
- It is the weighted average of the values that X can take, with weights given by the probability density function.
- The mean is known as expected value or expectation of X.
- An important consequence of this is that the mean of any symmetric random variable (continuous or discrete) is always on the axis of symmetry of the distribution.
- For a continuous random variable, the mean is always on the axis of symmetry of the probability density function.
To solve this, set up a proportion, crossmultiply, and solve for x.
Let x = the unknown amount of cases in 60 minutes.
44x = 50(60)
44x = 3000
Divide both sides by 44 to isolate variable x
x = 3000 / 44
x ≈ 68.1818 (the 18s repeat forever)
Rounding to the closest case and assuming the rate stays constant, you would get approximately 68 cases in 60 minutes. If you need not round to the nearest case, you would get approximately 68.18 cases in 60 minutes.
Let x = the unknown amount of cases in 60 minutes.
44x = 50(60)
44x = 3000
Divide both sides by 44 to isolate variable x
x = 3000 / 44
x ≈ 68.1818 (the 18s repeat forever)
Rounding to the closest case and assuming the rate stays constant, you would get approximately 68 cases in 60 minutes. If you need not round to the nearest case, you would get approximately 68.18 cases in 60 minutes.