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Chapter 6: The Normal Distribution 6.1 Probability Model for a Continuous Random Variable In the previous chapters, we have focused on discrete random variables. We now turn our attention to continuous random variables. Recall that a continuous random variable has infinitely many values that can be plotted on a line in an uninterrupted fashion. Continuous random variables are variables that result from measurement. The probability distribution of a discrete random variable can be represented by boxes on a histogram. The area of the box represented the probability of the associated value. With a continuous random variable, these boxes are “replaced” with curves. The curve is referred as the probability density curve. The mathematical function f(x) whose graph produces this curve is called the probability density function. What does this mean?? The probability that a continuous random variable is between to value can be represented as the area under the probability density function on that interval. There are lots of different kinds of distributions. Here some of the common “shapes”. Statisticians often find it useful to convenient to convert random variables to a dimensionless scale. This is done by created a new variable, Z, with mean O and sd 1. 6.2 The Normal Distribution-Its General Features 6.3 The Standard Normal Distribution Examples 1. For the probability density function depicted at the right: a) Find P(2<X<3) b) find P(X>3) c) Find the median and the quartiles. 2. Suppose Z has standard normal distribution. a.(6 points) Find P[Z > −1.02]andP[Z ≥ −1.02] b.(6 points) Find P[−1< Z < 2] c. (8 points) Determine the value of a so that P[−a < Z < a] = 0.95 3. For the standard normal variable, Z, find: a) P(Z > -1.79) b) z such that P(-.6 < Z < z)=.5 c) The 40th percentile of the standard normal distribution. 4) a) Find the 80th percentile of the standard normal distribution. b.) Find z such that P(-1 < Z < z) =.5 5.) Suppose Z has the standard normal distribution. Find: a) P( Z > 1.42 ) b) P( -2.01 < Z < 0.07) Find the z-value for the following: c) P( -z < Z < z) =.6372 d) P(0< Z < z) =0.4099. 6.4 Probability Calculations with Normal Distributions Example 1. Given that X has the normal distribution N(60,4), find P[55<X<63]. Here the standard variable is Z=(X-‐60)/4. 2. The meat department at a certain supermarket chain prepares “1 pound” packages of ground beef so that there will be a variety of weights, some slightly more and some slightly less than the 1 pound. Suppose that the weights of these 1 pound packages are normally distributed with a mean of 1.00 pound and a standard deviation of .15 pound. a) What is the probability that a randomly selected package of ground beef will weigh more than 1.2 pounds? b) What proportion of the packages will weigh between .95 and 1.10 pounds? 3. According to the Educational Testing Service, SAT scores are normally distributed with a mean of 1000 and a standard deviation of 200. a) Find the probability that a random test taker scores above 1324. b) Find the probability that a random test taker scores in the range 950 to 1250. c) Molly has scored in the 85th percentile. This means that she scored higher than 85% of all test takers. What was her score? 4. A survey finds that students at a university use computers an average of 7 hours per week with standard deviation 1 hour per week. Assume that the number of hours spent at a computer is normally distributed. If a student is randomly selected, find: a) the probability that the student uses a computer less than 4.5 hours per week. b) the probability that the student uses a computer between 4.5 and 9.5 hours per week. c) Find the proportion of students that use a computer more than 6 hours per week. 5. The length of a jump of a long jumper is normally distributed with a mean 28.4 feet and variance of .09. a) The world record long jump is 29.4 feet. What is the probability that the long jumper will break the world record on his next jump? b) Suppose that the long jumper’s next jump must be at least x feet to qualify for the Olympics. If the probability the jumper qualifies is .9319, then what is x? 6. The incandescent light bulbs made by a company has a mean lifetime of 1000 hours and standard deviation of 250 hours. Assume that the lifetime of light bulbs admits a normal distribution. a) The company claims that the lifetime of its light bulbs is from 750 hours to 1500 hours. What percentage of the light bulbs actually fall into this range? b) What is the minimum lifetime for a light builb in the top 1% of the total in terms of lifetime? 6.5 The Normal Approximation to the Binomial In a binomial experiment when the number of trials, n, the binomial probability formula can be difficult to use. For example, suppose there are 500 trials of a binomial experiment and we wish to compute the probability of 400 or more successes. Using the binomial probability formula requires that we compute the following probabilities: P(X≥400)=P(X=400)+P(X=401)+P(X=402)+…+P(X=500). This would be time consuming to compute by hand or with a calculator. As the number of trials, n, in a binomial experiment increases, the probability histogram becomes more nearly symmetric and bell shaped. (See Project 3). As the number of trials n in a binomial experiment increases, the probability distribution of the random variable X becomes more nearly symmetric and bell shaped. As a rule of thumb, if np ≥ 15 and n(1-p) ≥ 15, the probability distribution will be approximately symmetric and bell shaped. **The normal approximation to the binomial was discovered by Abraham de Moivre in 1733. Normal Approximation to Binomial Distribution 1. Suppose 20% of the children in a town have a certain virus. a. Estimate the probability that, in a random sample of 300 children, the number of children with the virus will be between 50 and 70 inclusive. b. Briefly justify your approximation procedure. 2. A survey report states that 20% of college seniors support an increase in federal funding care of the elderly. a) What is the approximate distribution of the random variable X=number of people that support an increase in federal funding care of the elderly? b) If 80 college seniors are randomly selected, use the approximation of part a) to find the probability that less than 6 of them support increased funding. 3. Suppose an operation has a 65% chance of success and is performed on a group of individuals. a) If the operation is performed on 6 people what is the probability that it is successful on exactly 4 people? b) If the operation is performed on 200 people use the normal approximation to the binomial to find the probability that it is successful on 150 or fewer people. Round Z values to two decimal digits so that the standard normal table look up does not require interpolation. 4. In a certain city, 20% of the students play sports. (a) In a random sample of 20 students from this city, what is the probability at least 5 play sports? (b) In a random sample of 200 students from this city, approximately what is the probability at most 45 play sports? 5. Only 30% of the people in a large city feel that its mass transit system is adequate. a) what is the approximate distribution of the random variable X=numer of people that feel the system is adequate? b) If 70 people are selected at random, use the approximation in (a) to find the probability that the number of people that feel the system is adequate is less than 10. 6. 60% of flights at an airport depart on time. Determine the probability that of 14 randomly selected flights: a) at least 6 depart on time. b) at most 5 do not depart on time. c) exactly 8 depart on time. d) Use the normal approximation to find the approximate probability that out of 350 randomly selected flights, less than 200 depart on time. Central Limit Theorem 1. A software company takes on average 150 days to complete a project, with a standard deviation of 20 days. For a random sample of 100 projects, let X denote the average time to complete the project. (a) What is the mean of X? (b) What is the standard deviation of X? (c) Estimate the probability that X lies between 145 and 155. (d) Briefly justify your answer to (c).