here this is is binomial distribution for which parameter n=10 and p=0.05
we are assuming that sample is random ; and probability of one product being defective is independent of other product.
P(full inspection)=P(2 or more defective)=P(X>=2)=1-P(X<=1)=1-(P(X=0)+P(X=1))
=1-10C0(0.05)0(0.95)10-10C1(0.05)1(0.95)9 =0.0861
A sample of 10 is taken from a day's output of a machine that produces parts...
A machine produces an average of 10% defective bolts. A batch is accepted if a sample of five bolts taken from the batch that contains no defective and rejected if the sample contains 3 or more defectives. In other cases, a second sample is taken. 1- ehatvis rhe probability that the second sample will be required 2- what Is the probability that the sample is rejected 3- if 15 bolts are taken from a batch, how many bolts are defective
a production process produces 4% defective parts. a sample of six parts from the production process is selected. what is the probability that the sample contains more than one defective parts
A machine that manufactures automobile parts produces defective parts 13% of the time. If 10 parts produced by this machine are randomly selected, what is the probability that at least 2 of the parts are defective? Carry your intermediate computations to at least four decimal places, and round your answer to at least two decimal places.
6) If 10% of the parts produced by a machine are defective, find the probability of at least one defective part in a random sample of five. Use probability notation to solve this problem.
6) If 10% of the parts produced by a machine are defective, find the probability of at least one defective part in a random sample of five. Use probability notation to solve this problem.
:Among 20 metal parts produced in a machine shop, 5 are defective. If a random sample of three of these metal parts is selected, find: 1. The probability that this sample will contain at least two defectives? 2. The probability that this sample will contain at most one defective? Note: Use hypergeometric probability formula
A sample of 200 machined parts is selected from the 1-week production of a machine shop that employs three machinists. The parts are inspected to determine whether they are defective, and they are categorized according to which machine did the work. The observed counts are given in Table. We want to determine the independence of defective/nondefective classification and machinist classification at the 1% significance level. Observed (Expected) Cell Counts for Machinist A Machinist B Machinist C Defective 10 8 14...
In a factory, only two machines, A and B, manufacture washers. Neither machine is perfect: machine A produces defective washers 14% of the time, while machine B produces defectives 10% of the time. Machine B is more efficient than machine A and accounts for 80% of the total output of washers. For purposes of quality control, a sample of washers is taken and examined for defectives. Compute the probability that a randomly chosen washer found to be defective was manufactured...
5. A certain production process produces 20 defective parts out of 200. An engineer designs a change in the process which results in 8 defective parts out of 200. Take a two-sided approach to answer the following questions. (a) 5 Do these data indicate that there is a difference in the support for decreasing pro- portion of defective parts due to changing the process? Find the P-value and report all relevant steps of the testing procedure. (b) Construct a 95%...
please show all work 1. 120 points! Four machines produce the total output of a factory, Machine 1 produces 30%, machine 2 produces 25% machine 3 produces 12% and machine 4 produces 13% of the output. 5% of the output of machine lis defective, 8% from machine 2 is not defective, 3% from machine 3 is defective and 4% from machine 4 is not defective. If a finished item is selected at rindom, a. What is the probability of it...