Answer to Question #119227 in Statistics and Probability for Stat

Question #119227
1. Raymond is a basketball player who takes four independent free throws with 70% probability of getting a basket on each shot. Let X be the number of baskets Raymond
gets. Find the probability that he gets exactly 2 baskets, to 3 decimal places.

2. The lifetime of a machine is continuous on the interval (0, 40) with probability density
function f, where f(t) is proportional to (t+ 10)^−2
, and t is the lifetime in years. Find
the proportionality constant that makes the f(t) a probability function.

3. Suppose John throws a die repeatedly until he gets a six. What is the probability that he needs to throw more than 10 times to get a six, to 3 decimal places?

4.A random variable X has Poisson distribution with mean equal to 0.4. What is the probability that the random variable is greater than zero?
1
Expert's answer
2020-06-01T18:15:45-0400

"1. \\ X\\sim Bin(n, p)"


"P(X=x)=\\binom{n}{k}p^x(1-p)^{n-x}"

Given "p=0.7,n=4"

"P(X=2)=\\binom{4}{2}(0.7)^2(1-0.7)^{4-2}=""={4!\\over 2!(4-2)!}(0.21)^2=0.2646\\approx0.265"

2. Since "f(t)" is proportional to "(10+t)^{-2}" on the interval "(0,40)," we conclude that there is a positive constant "C" such that


"f(t) = \\begin{cases}\n C(10+t)^{-2} &\\text{if } t\\in(0,40) \\\\\n 0, &\\text{otherwise} \n\\end{cases}"

We can determine the proportionality constant "C" from the condition "\\displaystyle\\int_{-\\infin}^{\\infin}f(t)dt=1,"

which must be satisfied because "f(t)" is a density. We have


"1=\\displaystyle\\int_{-\\infin}^{\\infin}f(t)dt=\\displaystyle\\int_{0}^{40}C(10+t)^{-2}dt=""=-C\\bigg[{1\\over 10+t}\\bigg]\\begin{matrix}\n 40 \\\\\n 0\n\\end{matrix}=C(-{1\\over 50}+{1\\over 10})={2\\over 25}C"

Therefore "C=12.5."


"f(t) = \\begin{cases}\n 12.5(10+t)^{-2} &\\text{if } t\\in(0,40) \\\\\n 0, &\\text{otherwise} \n\\end{cases}"

3. Geometric distribution

If repeated independent trials can result in a success with probability "p" and a failure with probability "q=1-p," then the probability distribution of the random variable "X," the number of the trial on which the first success occurs, is


"g(x;p)=p(1-p)^{x-1}, x=1,2,3,..."

Given "p=\\dfrac{1}{6}"


"P(X=1)={1 \\over 6}(1-{1 \\over 6})^0={1 \\over 6}""P(X=2)={1 \\over 6}(1-{1 \\over 6})^1={1 \\over 6}({5 \\over 6})^1""...""P(X=10)={1 \\over 6}(1-{1 \\over 6})^{9}={1 \\over 6}({5 \\over 6})^{9}"

"P(X\\leq10)=\\displaystyle\\sum_{i=1}^{10}P(X=x_i)={1 \\over 6}\\displaystyle\\sum_{i=1}^{10}({5 \\over 6})^{i-1}=""={1 \\over 6}\\cdot\\dfrac{1-({5 \\over 6})^{10}}{1-{5\\over 6}}=1-({5 \\over 6})^{10}""P(X>10)=1-P(X\\leq10)=({5 \\over 6})^{10}\\approx0.162"

4.

"P(X=x)={e^{-\\mu}\\cdot \\mu^x \\over x!}"

Given "\\mu=0.4"


"P(X=0)={e^{-0.4}\\cdot 0.4^0 \\over 0!}=e^{-0.4}"

"P(X>0)=1-P(X=0)=1-e^{-0.4}\\approx0.330"


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