. A normally distributed population has mean 57,800 and standard deviation 750.
a. Find the probability that a single randomly selected element X of the population is between 57,000 and 58,000.
b. Find the mean and standard deviation of 𝑥̅for samples of size 100.
c. Find the probability that the mean of a sample of size 100 drawn from this population is between 57,000 and 58,000.
We are given that a normally distributed population has mean 57,800 and standard deviation 75, i.e.; "\\mu = 57800" and "\\sigma=750" .
Let X = randomly selected element of the population
The z probability is given by;
Z = "\\frac{X-\\mu}{\\sigma}" ~ N(0,1)
a. So, P(57,000 <= X <= 58,000) = P(X <= 58,000) - P(X < 57,000)
P(X <= 58,000) = P( "\\frac{X-\\mu}{\\sigma}" <= "\\frac{58000-57800}{750}" ) = P(Z <= 0.27) = 0.60642
P(X < 57000) = P( "\\frac{X-\\mu}{\\sigma}" < "\\frac{57000-57800}{750}" ) = P(Z < -1.07) = 1 - P(Z <= 1.07) = 1 - 0.85769 = 0.14231
Therefore, P(31 < X < 40) = 0.60642 - 0.14231 = 0.46411 .
b. Now, we are given sample of size, n = 100
So, Mean of X, "\\overline{X}" = 57,800 same as before
But standard deviation of X, s = "\\frac{\\sigma}{\\sqrt{n}}" = "\\frac{750}{\\sqrt{100}}" = 75
c. The z probability is given by;
Z = "\\frac{\\overline{X}-\\mu}{s}" ~ N(0,1)
Now, probability that the mean of a sample of size 100 drawn from this population is between 57,000 and 58,000 = P(57,000 < "\\overline{X}" < 58,000)
P(57,000 <= "\\overline{X}" <= 58,000) = P("\\overline{X}" <= 58,000) - P("\\overline{X}" < 57,000)
P("\\overline{X}" <= 58,000) = P( "\\frac{\\overline{X}-\\mu}{s}" <= "\\frac{58000-57800}{75}" ) = P(Z <= 2.67) = 0.99621
P(X < 57000) = P( "\\frac{\\overline{X}-\\mu}{s}" < "\\frac{57000-57800}{75}") = P(Z < -10.67) = P(Z > 10.67)
This probability is that much small that it is very close to 0
Therefore, P(57,000 < X bar < 58,000) = 0.99621 - 0 = 0.99621 .
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