4. Assume that the mean life of a particular brand of car battery is normally distributed with a mean of 28 months and a standard variation of 4 months.
(a) for a randomly selected battery of this make, what is the probability that it will last between 30 and 34 months?.
(b) what is the probability that a randomly selected battery of this make will fail within years of date of purchase?.
(c) after what time period will 60% of all batteries of this makes fail?.
We denote the respective random variable (life of battery) by "X". We remind that for the normal distribution with parameters "\\mu=28" and "\\sigma=4" the probability density function is "p(x)=\\frac{1}{\\sigma\\sqrt{2\\pi}}e^{-\\frac{1}{2}\\left(\\frac{x-\\mu}{\\sigma}\\right)^2}"
(a) "P(30\\leq X\\leq34)=\\int_{30}^{34}p(x)dx=\\frac{1}{\\sigma\\sqrt{2\\pi}}\\int_{30}^{34}e^{-\\frac{1}{2}\\left(\\frac{x-\\mu}{\\sigma}\\right)^2}dx\\approx0.2417"
We computed the integral using the following code in Anaconda(https://www.anaconda.com/):
from scipy import integrate
import numpy as np
import math
func = lambda x:(1/(4*math.sqrt(2)*math.sqrt(math.pi)))*math.exp(-1/2*((x-28)/4)*((x-28)/4))
e = integrate.quad(func, 30, 34)
print(e)
(b) We assume that the time is 1 year. We get: "P(-\\infty\\leq X\\leq12)=\\int_{-\\infty}^{12}p(x)dx=\\frac{1}{\\sigma\\sqrt{2\\pi}}\\int_{-\\infty}^{12}e^{-\\frac{1}{2}\\left(\\frac{x-\\mu}{\\sigma}\\right)^2}dx\\approx0.00003167"
(c) The aim is to find such "\\alpha" that: "P(-\\infty\\leq X\\leq\\alpha)=\\frac{1}{\\sigma\\sqrt{2\\pi}}\\int_{-\\infty}^{\\alpha}e^{-\\frac{1}{2}\\left(\\frac{x-\\mu}{\\sigma}\\right)^2}dx=0.4" It means that the battery will fail with the probability 60%. We get that "\\alpha\\approx26.99". We received "\\alpha" by substituting different values in the code (Anaconda):
from scipy import integrate
import numpy as np
import math
func = lambda x:(1/(4*math.sqrt(2)*math.sqrt(math.pi)))*math.exp(-1/2*((x-28)/4)*((x-28)/4))
e = integrate.quad(func, -np.inf, 26.99)
print(e)
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