Suppose you are a production manager for a small firm that manufactures designer phone cases. Your production facility utilizes three machines. Quality is binary — each phone case is either defective or it is not defective. Each hour, Machines 1, 2, and 3 produce 10, 10 and 20 phone cases, respectively. But because the machines differ slightly in their technology, data on past production has shown that they differ in terms of their rates of defective output — specifically, Machines 1, 2, and 3 have rates of defective production of 2%, 4%, and 5%, respectively. If one phone case is selected

Suppose you are a production manager for a small firm that manufactures designer phone cases. Your production facility utilizes three machines. Quality is binary — each phone case is either defective or it is not defective. Each hour, Machines 1, 2, and 3 produce 10, 10 and 20 phone cases, respectively. But because the machines differ slightly in their technology, data on past production has shown that they differ in terms of their rates of defective output — specifically, Machines 1, 2, and 3 have rates of defective production of 2%, 4%, and 5%, respectively. If one phone case is selected

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter2: Systems Of Linear Equations

Section2.4: Applications

Problem 28EQ

See similar textbooks

Similar questions

If during the following year it is predicted that each comedy skit will generate 30 thousand and each musical number 20 thousand, find the maximum income for the year. A television program director must schedule comedy skits and musical numbers for prime-time variety shows. Each comedy skit requires 2 hours of rehearsal time, costs 3000, and brings in 20,000 from the shows sponsors. Each musical number requires 1 hour of rehearsal time, costs 6000, and generates 12,000. If 250 hours are available for rehearsal and 600,000 is budgeted for comedy and music, how many segments of each type should be produced to maximize income? Find the maximum income.
2. Suppose that in Example 2.27, 400 units of food A, 500 units of B, and 600 units of C are placed in the test tube each day and the data on daily food consumption by the bacteria (in units per day) are as shown in Table 2.7. How many bacteria of each strain can coexist in the test tube and consume all of the food? Table 2.7 Bacteria Strain I Bacteria Strain II Bacteria Strain III Food A 1 2 0 Food B 2 1 3 Food C 1 1 1
The compressors used in refrigerators are manufactured by XYZ Co. at three factories at New York , and California, It is known that the New York factory produces twice as many compressors as the California one, Which produces the same number as the California one (during the same period). Experience also shows That 0.2% of the compressors produced at New York and California are defective and so are 0.4% of these Produced at California. A quality control engineer while maintaining a refrigerator finds a defective compressor. What is the probability that the New York factory is not to be blamed.
Wenton Powersports produces dune buggies. They have three assembly lines, “Razor,” “Blazer,” and “Tracer,” named after the particular dune buggy models produced on those lines. Each assembly line was originally designed using the same target production rate. However, over the years, various changes have been made to the lines. Accordingly, management wishes to determine whether the assembly lines are still operating at the same average hourly production rate. Production data (in dune buggies/hour) for the last eight hours are as follows. (You may find it useful to reference the F table.) (Inserted image is the table) a. Specify the competing hypotheses to test whether there are some differences in the mean production rates across the three assembly lines. (which one is correct) H0: μRazor = μBlazer = μTracer. HA: Not all population means are equal. H0: μRazor ≤ μBlazer ≤ μTracer. HA: Not all population means are equal. H0: μRazor ≥ μBlazer ≥ μTracer. HA: Not all…
You're a quality engineer at Norman's fouth largest cracker factory. where there are two production lines (A, which produces 20% of cracker boxes, and B which produces the rest). If a line produces more than one defective box in an eight -hour day, a maintenance check on the line is performed. Line A produces an average of 0.061 box defects PER Hour. Given that you're only looking at a line A, what is the probability that you will need a request a maitenance check.
The owner of a chain of mini-markets wants to compare the sales performance of two of her stores, Store 1 and Store 2. Sales can vary considerably depending on the day of the week and the season of the year, so she decides to eliminate such effects by making sure to record each store's sales on the same 8 days, chosen at random. She records the sales (in dollars) for each store on these days, as shown in the table below. Day Store 1 Store 2 1 467 Difference (Store 1 - Store 2) Send data to calculator V 361 Explanation Check 106 2 865 903 - 38 3 254 4 704 5 929 102 611 671 6 418 550 7 (a) State the null hypothesis H and the alternative hypothesis H₁. Ho : D 734 737 152 93 258 - 132 -3 8 621 690 Based on these data, can the owner conclude, at the 0.10 level of significance, that the mean daily sales of the two stores differ? Answer this question by performing a hypothesis test regarding μd (which is u with a letter "d" subscript), the population mean daily sales difference between the…
The owner of a chain of mini-markets wants to compare the sales performance of two of her stores, Store 1 and Store 2. Sales can vary considerably depending on the day of the week and the season of the year, so she decides to eliminate such effects by making sure to record each store's sales on the same 8 days, chosen at random. She records the sales (in dollars) for each store on these days, as shown in the table below. Day Store 1 Store 2 1 889 2 Difference (Store 1 - Store 2) Send data to calculator V 3 699 534 479 525 252 4 398 5 432 364 160 6 7 8 213 252 929 32 234 632 410 174 282 34 272 181 18 297 Based on these data, can the owner conclude, at the 0.10 level of significance, that the mean daily sales of the two stores differ? Answer this question by performing a hypothesis test regarding μ (which is u with a letter "d" subscript), the population mean daily sales difference between the two stores. Assume that this population of differences (Store 1 minus Store 2) is normally…
A manufacturing company is analyzing its accident record. The accidents fall into two categories: Minor—dealt with by first aider: Average cost k50 Major—hospital required. Average cost k1,000The company has 1,000 employees, of which 180 are office staff and the rest work in the factory.The analysis shows that 10% of employees have an accident each year and 20% of accidents are major. It is assumed that an employee has more than one accident in a year.(i) Determine the expected total cost of accidents in a year. On further analysis it is discovered that a member of office staff has half the probability of having an accident relative those in the factory. (ii)Show that the probability that a given a member of office staff has an accident in a year is 0.0549.(iii) Determine the probability that a randomly chosen employee who has had an accident is office staff.
In his doctoral thesis, L. A. Beckel (University of Minnesota, 1982) studied the social behavior of river otters during the mating season. An important role in the bonding process of river otters is very short periods of social grooming. After extensive observations, Dr. Beckel found that one group of river otters under study had a frequency of initiating grooming of approximately 1.7 for each 10 minutes. Suppose that you are observing river otters for 40 minutes. Let r = 0, 1, 2, ... be a random variable that represents the number of times (in a 40-minute interval) one otter initiates social grooming of another. Lambda = 6.8 (b) Find the probabilities that in your 40 minutes of observation, one otter will initiate social grooming four times, five times, and six times. (Round your answers to four decimal places.) P(4) = P(5) = P(6) =
In his doctoral thesis, L. A. Beckel (University of Minnesota, 1982) studied the social behavior of river otters during the mating season. An important role in the bonding process of river otters is very short periods of social grooming. After extensive observations, Dr. Beckel found that one group of river otters under study had a frequency of initiating grooming of approximately 1.7 for each 10 minutes. Suppose that you are observing river otters for 30 minutes. Let r = 0, 1, 2, ... be a random variable that represents the number of times (in a 30-minute interval) one otter initiates social grooming of another. a) Find the probabilities that in your 30 minutes of observation, one otter will initiate social grooming four times, five times, and six times. (Round your answers to four decimal places.) P(4) = P(5) = P(6) = b) Find the probability that one otter will initiate social grooming less than four times during the 30-minute observation period. (Round your answer…
In his doctoral thesis, L. A. Beckel (University of Minnesota, 1982) studied the social behavior of river otters during the mating season. An important role in the bonding process of river otters is very short periods of social grooming. After extensive observations, Dr. Beckel found that one group of river otters under study had a frequency of initiating grooming of approximately 1.7 for each 10 minutes. Suppose that you are observing river otters for 30 minutes. Let r = 0, 1, 2, ... be a random variable that represents the number of times (in a 30-minute interval) one otter initiates social grooming of another. a) What is ?? b) Write out the formula for the probability distribution of the random variable r. P(r) = _________ c) Find the probability that one otter will initiate social grooming four or more times during the 30-minute observation period. (Round your answer to four decimal places.)