A batch of 500 machined parts contains 10 that do not conform to customer requirements. Parts are selected successively, without replacement, until a nonconforming part is obtained. The random variable is the number of parts selected.
> Determine the mean and variance of the random variable in Exercise 3.1.11.
> Determine the mean and variance of the random variable in Exercise 3.1.10.
> It is suspected that some of the totes containing chemicals purchased from a supplier exceed the moisture content target. Assume that the totes are independent with respect to moisture content. Determine the proportion of totes from the supplier that mus
> Saguaro cacti are large cacti indigenous to the southwesternUnited States and Mexico.Assume that the number of saguaro cacti in a region follows a Poisson distribution with a mean of 280 per square kilometer. Determine the following: a. Mean number of ca
> An installation technician for a specialized communication system is dispatched to a city only when three or more orders have been placed. Suppose that orders follow a Poisson distribution with a mean of 0.25 per week for a city with a population of 100,
> From 500 customers, a major appliance manufacturer randomly selects a sample without replacement. The company estimates that 25% of the customers will reply to the survey. If this estimate is correct, what is the probability mass function of the number o
> Each main bearing cap in an engine contains 4 bolts. The bolts are selected at random without replacement froma parts bin that contains 30 bolts from one supplier and 70 bolts from another. a. What is the probability that a main bearing cap contains all
> Assume that the number of errors along a magnetic recording surface is a Poisson random variable with amean of one error every 105 bits. A sector of data consists of 4096 eight-bit bytes. a. What is the probability of more than one error in a sector? b.
> The random variable X has the following probability distribution: Determine the following: a. P(X ≤ 3) b. P(X > 2.5) c. P(2.7 d. E(X) e. V(X)
> Suppose that the number of customers who enter a store in an hour is a Poisson random variable, and suppose that P(X = 0) = 0.05. Determine the mean and variance of X.
> Determine the probability mass function for the random variable with the following cumulative distribution function:
> A manufacturer of a consumer electronics product expects 2% of units to fail during the warranty period. A sample of 500 independent units is tracked for warranty performance. a. What is the probability that none fails during thewarranty period? b. What
> In a manufacturing process that laminates several ceramic layers, 1% of the assemblies are defective. Assume that the assemblies are independent. a. What is the mean number of assemblies that need to be checked to obtain five defective assemblies? b. Wha
> Patient response to a generic drug to control pain is scored on a 5-point scale where a 5 indicates complete relief. Historically, the distribution of scores is Two patients, assumed to be independent, are each scored. a. What is the probability mass fun
> The probability that an individual recovers from an illness in a one-week time period without treatment is 0.1. Suppose that 20 independent individuals suffering from this illness are treated with a drug and 4 recover in a one-week time period. If the dr
> The number of errors in a textbook follows a Poisson distribution with a mean of 0.01 error per page. What is the probability that there are three or fewer errors in 100 pages?
> The probability that your call to a service line is answered in less than 30 seconds is 0.75. Assume that your calls are independent. a. If you call 10 times, what is the probability that exactly nine of your calls are answered within 30 seconds? b. If y
> The number of messages that arrive at aWeb site is a Poisson random variable with a mean of five messages per hour. a. What is the probability that five messages are received in 1.0 hour? b. What is the probability that 10 messages are received in 1.5 ho
> Traffic flow is traditionally modeled as a Poisson distribution. A traffic engineer monitors the traffic flowing through an intersection with an average of six cars per minute. To set the timing of a traffic signal, the following probabilities are used.
> A shipment of chemicals arrives in 15 totes. Three of the totes are selected at random without replacement for an inspection of purity. If two of the totes do not conform to purity requirements, what is the probability that at least one of the nonconform
> The number of telephone calls that arrive at a phone exchange is often modeled as a Poisson random variable. Assume that on the average there are 10 calls per hour. Determine the following probabilities: a. exactly 5 calls in one hour b. 3 or fewer calls
> An electronic scale in an automated filling operation stops themanufacturing line after three underweight packages are detected. Suppose that the probability of an underweight package is 0.001 and each fill is independent. a. What is the mean number of f
> The probability that an eagle kills a rabbit in a day of hunting is 10%. Assume that results are independent for each day. a. What is the distribution of the number of days until a successful hunt? b. What is the probability that the first successful hu
> A particularly long traffic light on your morning commute is green on 20% of the mornings. Assume that each morning represents an independent trial. a. What is the probability that the first morning that the light is green is the fourth morning? b. What
> A congested computer network has a 1%chance of losing a data packet that must be resent, and packet losses are independent events. An e-mail message requires 100 packets. a. What is the distribution of the number of packets in an e-mail message that must
> An automated egg carton loader has a 1% probability of cracking an egg, and a customer will complain if more than one egg per dozen is cracked. Assume that each egg load is an independent event. a. What is the distribution of cracked eggs per dozen? Incl
> Let X denote the number of bits received in error in a digital communication channel, and assume that X is a binomial random variable with p = 0.001. If 1000 bits are transmitted, determine the following: a. P(X = 1) b. P(X ≥ 1) c. P(X ≤ 2) d. mean and
> Let the random variable X be equally likely to assume any of the values 1/8, 1/4, or 3/8. Determine the mean and variance of X.
> Consider the time to recharge the flash in cell-phone cameras as in Example 3.1. Assume that the probability that a camera passes the test is 0.8 and the cameras perform independently. What is the smallest sample size needed so that the probability of at
> The article “An Association Between Fine Particles and Asthma Emergency Department Visits for Children in Seattle” [Environmental Health Perspectives June 1999, Vol. 107(6)] used Poisson models for the number of asthma emergency department (ED) visits pe
> The probability that a visitor to aWeb site provides contact data for additional information is 0.01. Assume that 1000 visitors to the site behave independently. Determine the following probabilities: a. No visitor provides contact data. b. Exactly 10 vi
> An array of 30 LED bulbs is used in an automotive light. The probability that a bulb is defective is 0.001 and defective bulbs occur independently. Determine the following: a. Probability that an automotive light has two or more defective bulbs. b. Expec
> Customers visit aWeb site, and the probability of an order if a customer views five or fewer pages is 0.01. However, if a customer views more than five pages, the probability of an order is 0.1. The probability a customer views five or more pages is 0.25
> Consider the time to recharge the flash in cell-phone cameras as in Example 3.1. Assume that the probability that a camera passes the test is 0.8 and the cameras perform independently. Determine the following: a. Probability that the second failure occur
> If the range of X is the set {0, 1, 2, 3, 4} and P(X = x) = 0.2, determine the mean and variance of the random variable.
> a. P(X ≤ 50) b. P(X ≤ 40) c. P(40 ≤ X ≤ 60) d. P(X e. P(0 ≤ X f. P(−10
> a. P(X ≤ 3) b. P(X ≤ 2) c. P(1 ≤ X ≤ 2) d. P(X > 2)
> Determine the cumulative distribution function for the random variable in Exercise 3.1.16.
> Determine the cumulative distribution function for the random variable in Exercise 3.1.13.
> Determine the cumulative distribution function for the random variable in Exercise 3.1.12; also determine the following probabilities: a. P(X < 1.5) b. P(X ≤ 3) c. P(X > 2) d. P(1 < X ≤ 2)
> Cabs pass your workplace according to a Poisson process with a mean of five cabs per hour. Suppose that you exit the workplace at 6:00 P.M. Determine the following: a. Probability that you wait more than 10 minutes for a cab. b. Probability that you wait
> Determine the cumulative distribution function for the random variable in Exercise 3.1.11.
> Determine the cumulative distribution function of the random variable in Exercise 3.1.10.
> Determine the cumulative distribution function for the random variable in Exercise 3.1.9.
> A healthcare provider schedules 30 minutes for each patient’s visit, but some visits require extra time. The random variable is the number of patients treated in an eight-hour day.
> The number of mutations in a nucleotide sequence of length 40,000 in a DNA strand after exposure to radiation is measured. Each nucleotide may be mutated.
> A group of 10,000 people are tested for a gene called Ifi202 that has been found to increase the risk for lupus. The random variable is the number of people who carry the gene.
> The random variable is the number of surface flaws in a large coil of galvanized steel.
> The random variable is the number of computer clock cycles required to complete a selected arithmetic calculation.
> A batch of 500 machined parts contains 10 that do not conform to customer requirements. The random variable is the number of parts in a sample of five parts that do not conform to customer requirements.
> Inclusions are defects in poured metal caused by contaminants. The number of (large) inclusions in cast iron follows a Poisson distribution with a mean of 2.5 per cubic millimeter. Determine the following: a. Probability of at least one inclusion in a cu
> Suppose that X has a Poisson distribution. Determine the following probabilities when the mean of X is 4 and repeat for a mean of 0.4: a. P(X = 0) b. P(X ≤ 2) c. P(X = 4) d. P(X = 8)
> What is the difference between a confidence interval estimate of the mean response, μY|X = Xi, and a prediction interval of YX = Xi?
> When and how do you use the Durbin-Watson statistic?
> How do you evaluate the assumptions of regression analysis?
> What are the assumptions of regression analysis?
> Why should you always carry out a residual analysis as part of a regression model?
> Use the following information from a multiple regression analysis: n = 20 b1 = 4 b2 = 3 Sb1 = 1.2 Sb2 = 0.8 a. Which variable has the largest slope, in units of a t statistic? b. Construct a 95% confidence interval estimate of the population slope, b1.
> When is the explained variation (i.e., regression sum of squares) equal to 0?
> When is the unexplained variation (i.e., error sum of squares) equal to 0?
> What is the interpretation of the coefficient of determination?
> What is the interpretation of the Y intercept and the slope in the simple linear regression equation?
> Assume that you are working with the results from Problems 11.15 and 11.16. a. What is the value of the FSTAT test statistic for the interaction effect? b. What is the value of the FSTAT test statistic for the factor A effect? c. What is the value of the
> In Problem 13.10 on page 494, you used YouTube trailer views to predict movie weekend box office gross from data stored in Movie . A movie, about to be released, has 50 million YouTube trailer views. a. What is the predicted weekend box office gross? b
> In Problem 13.8 on page 494, you predicted the value of a baseball franchise, based on current revenue. The data are stored in BBValues . a. Construct a 95% confidence interval estimate of the mean value of all baseball franchises that generate $250 mil
> In Problem 13.9 on page 494, an agent for a real estate company wanted to predict the monthly rent for one-bedroom apartments, based on the size of an apartment. The data are stored in RentSilverSpring . a. Construct a 95% confidence interval estimate of
> In Problem 13.6 on page 494, a prospective MBA student wanted to predict starting salary upon graduation, based on program per-year tuition. The data are stored in FTMBA . a. Construct a 95% confidence interval estimate of the mean starting salary upon
> In Problem 13.7 on page 494, you used the plate gap on the bag-sealing equipment to predict the tear rating of a bag of coffee. The data are stored in Starbucks . a. Construct a 95% confidence interval estimate of the mean tear rating for all bags of co
> In Problem 13.4 on page 493, you used the percentage of alcohol to predict wine quality. The data are stored in VinhoVerde . For these data, SYX = 0.9369 and hi = 0.024934 when X = 10. a. Construct a 95% confidence interval estimate of the mean wine qual
> Use the following information from a multiple regression analysis: n = 25 b1 = 5 b2 = 10 Sb1 = 2 Sb2 = 8 a. Which variable has the largest slope, in units of a t statistic? b. Construct a 95% confidence interval estimate of the population slope, b1. c. A
> In Problem 13.5 on page 493, you used the summated rating of a restaurant to predict the cost of a meal. The data are stored inRestaurants . a. Construct a 95% confidence interval estimate of the mean cost of a meal for restaurants that have a summated r
> Based on a sample of n = 20, the least-squares method was used to develop the following prediction line: In addition, a. Construct a 95% confidence interval estimate of the population mean response for X = 4. b. Construct a 95% prediction interval o
> Based on a sample of n = 20, the least-squares method was used to develop the following prediction line: In addition, a. Construct a 95% confidence interval estimate of the population mean response for X = 2. b. Construct a 95% prediction interval o
> Assume that you are working with the results from Problem 11.15, and SSA = 120, SSB = 110, SSE = 270, and SST = 540. a. What is SSAB? b. What are MSA and MSB? c. What is MSAB? d. What is MSE? Problem 11.15: Consider a two-factor factorial design with th
> A survey by the Pew Research Center found that social networking is popular in many nations around the world. The file GlobalSocialMedia contains the level of social media networking (measured as the percent of individuals polled who use social networkin
> The file MobileSpeed contains the overall download and upload speeds in mbps for nine carriers in the United States. Source: Data extracted from “Best Mobile Network 2016,” bit.ly/1KGPrMm, accessed November 10, 2016. a. Compute and interpret the coeffi
> Movie companies need to predict the gross receipts of an individual movie once the movie has debuted. The following results (stored in PotterMovies ) are the first weekend gross, the U.S. gross, and the worldwide gross (in $millions) of the eight Harry P
> The file Cereals contains the calories and sugar, in grams, in one serving of seven breakfast cereals: a. Compute and interpret the coefficient of correlation, r. b. At the 0.05 level of significance, is there a significant linear relationship between
> Index funds are mutual funds that try to mimic the movement of leading indexes, such as the S&P 500 or the Russell 2000. The beta values (as described in Problem 13.49) for these funds are therefore approximately 1.0, and the estimated market models
> The volatility of a stock is often measured by its beta value. You can estimate the beta value of a stock by developing a simple linear regression model, using the percentage weekly change in the stock as the dependent variable and the percentage weekly
> In Problem 13.10 on page 494, you used YouTube trailer views to predict movie weekend box office gross from data stored in Movie . Use the results of that problem. a. At the 0.05 level of significance, is there evidence of a linear relationship between Y
> In Problem 14.8 on page 542, you used the land area of a property and the age of a house to predict the fair market value (stored in GlenCove ). a. Perform a residual analysis on your results. b. If appropriate, perform the Durbin-Watson test, using a =
> In Problem 13.9 on page 494, an agent for a real estate company wanted to predict the monthly rent for one-bedroom apartments, based on the size of the apartment. The data are stored in RentSilverSpring . Use the results of that problem. a. At the 0.05 l
> In Problem 13.8 on page 494, you used annual revenues to predict the value of a baseball franchise. The data are stored in BBValues . Use the results of that problem. a. At the 0.05 level of significance, is there evidence of a linear relationship betwee
> Consider a two-factor factorial design with three levels for factor A, three levels for factor B, and four replicates in each of the nine cells. a. How many degrees of freedom are there in determining the factor A variation and the factor B variation? b.
> In Problem 13.7 on page 494, you used the plate gap in the bag-sealing equipment to predict the tear rating of a bag of coffee. The data are stored in Starbucks . Use the results of that problem. a. At the 0.05 level of significance, is there evidence of
> In Problem 13.6 on page 494, a prospective MBA student wanted to predict starting salary upon graduation, based on program per-year tuition. The data are stored in FTMBA . Use the results of that problem. a. At the 0.05 level of significance, is there ev
> In Problem 13.5 on page 493, you used the summated rating of a restaurant to predict the cost of a meal. The data are stored in Restaurants . a. At the 0.05 level of significance, is there evidence of a linear relationship between the summated rating of
> In Problem 13.4 on page 493, you used the percentage of alcohol to predict wine quality. The data are stored in VinhoVerde . From the results of that problem, b1 = 0.5624 and Sb1 = 0.1127. a. At the 0.05 level of significance, is there evidence of a line
> You are testing the null hypothesis that there is no linear relationship between two variables, X and Y. From your sample of n = 20, you determine that SSR = 60 and SSE = 40. a. What is the value of FSTAT? b. At the a = 0.05 level of significance, what i
> You are testing the null hypothesis that there is no linear relationship between two variables, X and Y. From your sample of n = 18, you determine that b1 = +4.5 and Sb1 = 1.5. a. What is the value of tSTAT? b. At the α = 0.05 level of significance, wh
> You are testing the null hypothesis that there is no linear relationship between two variables, X and Y. From your sample of n = 10, you determine that r = 0.80. a. What is the value of the t test statistic tSTAT? b. At the α = 0.05 level of significan
> The owners of a chain of ice cream stores have the business objective of improving the forecast of daily sales so that staffing shortages can be minimized during the summer season. As a starting point, the owners decide to develop a simple linear regress
> In Problem 14.7 on page 542, you used the weekly staff count and remote engineering hours to predict standby hours (stored in Nickels26Weeks ). a. Perform a residual analysis on your results. b. If appropriate, perform the Durbin-Watson test, using a = 0
> A transportation strategist wanted to compare the traffic congestion levels across four continents: Asia, Europe, North America, and South America. The file CongestionLevel contains congestion level, defined as the increase (%) in overall travel time whe
> A mail-order catalog business that sells personal computer supplies, software, and hardware maintains a centralized warehouse for the distribution of products ordered. Management is currently examining the process of distribution from the warehouse and h
> In Problem 13.7 on page 494 concerning the bag-sealing equipment at Starbucks, you used the plate gap to predict the tear rating. a. Is it necessary to compute the Durbin-Watson statistic in this case? Explain. b. Under what circumstances is it necessary
> The residuals for 15 consecutive time periods are as follows: a. Plot the residuals over time. What conclusion can you reach about the pattern of the residuals over time? b. Compute the Durbin-Watson statistic. At the 0.05 level of significance, is the
> The residuals for 10 consecutive time periods are as follows: a. Plot the residuals over time. What conclusion can you reach about the pattern of the residuals over time? b. Based on (a), what conclusion can you reach about the autocorrelation of the r
> In Problem 13.10 on page 494, you used YouTube trailer views to predict movie weekend box office gross. Perform a residual analysis for these data (stored in Movie ). Based on these results, evaluate whether the assumptions of regression have been seriou
