document.write( "Question 1193442: A shipment of 10 items has two defective and eight non defective units. In the inspection of the shipment , a sample of units will be selected and tested. If a defective unit is found , the shipment of 10 units will be rejected.If management would like a .90 probability of rejecting a shipment with two defective and eight non defective units , how large a sample would you recommend ? \n" ); document.write( "
Algebra.Com's Answer #848805 by CPhill(1959)![]() ![]() You can put this solution on YOUR website! **1. Define the Probability of Rejection:**\r \n" ); document.write( "\n" ); document.write( "* The probability of rejecting a shipment is the probability of finding at least one defective unit in the sample.\r \n" ); document.write( "\n" ); document.write( "**2. Calculate the Probability of Not Rejecting:**\r \n" ); document.write( "\n" ); document.write( "* The probability of not rejecting a shipment is the probability of finding no defective units in the sample.\r \n" ); document.write( "\n" ); document.write( "**3. Determine the Sample Size:**\r \n" ); document.write( "\n" ); document.write( "* We need to find the sample size (n) that satisfies the following condition: \n" ); document.write( " Probability of rejecting the shipment ≥ 0.90 \n" ); document.write( " 1 - Probability of not rejecting the shipment ≥ 0.90 \n" ); document.write( " Probability of not rejecting the shipment ≤ 0.10\r \n" ); document.write( "\n" ); document.write( "**4. Calculate the Probability of Not Rejecting (for a given sample size n):**\r \n" ); document.write( "\n" ); document.write( "* The probability of not rejecting a shipment is the probability of selecting only non-defective units in the sample. \n" ); document.write( "* This can be calculated using the hypergeometric distribution:\r \n" ); document.write( "\n" ); document.write( " Probability of not rejecting = (Number of ways to choose n non-defective units from 8 non-defective units) / (Total number of ways to choose n units from 10 total units) \n" ); document.write( " Probability of not rejecting = (8Cn) / (10Cn) \r \n" ); document.write( "\n" ); document.write( "**5. Find the Sample Size (n) by Trial and Error:**\r \n" ); document.write( "\n" ); document.write( "* Start with a small sample size (e.g., n = 1) and calculate the probability of not rejecting. \n" ); document.write( "* Increase the sample size gradually and recalculate the probability until the probability of not rejecting is less than or equal to 0.10.\r \n" ); document.write( "\n" ); document.write( "**Using a Spreadsheet or Statistical Software:**\r \n" ); document.write( "\n" ); document.write( "* You can use a spreadsheet program (like Excel) or statistical software (like R or Python) to efficiently calculate the hypergeometric probabilities for different sample sizes. This will help you quickly find the minimum sample size that meets the desired rejection probability.\r \n" ); document.write( "\n" ); document.write( "**Example (Illustrative):**\r \n" ); document.write( "\n" ); document.write( "* **n = 1:** Probability of not rejecting = (8C1) / (10C1) = 0.8 \n" ); document.write( "* **n = 2:** Probability of not rejecting = (8C2) / (10C2) = 0.56 \n" ); document.write( "* **n = 3:** Probability of not rejecting = (8C3) / (10C3) = 0.3 \n" ); document.write( "* **n = 4:** Probability of not rejecting = (8C4) / (10C4) = 0.1429 \n" ); document.write( "* **n = 5:** Probability of not rejecting = (8C5) / (10C5) = 0.051 \r \n" ); document.write( "\n" ); document.write( "In this example, a sample size of **n = 5** would likely satisfy the requirement, as the probability of not rejecting is less than 0.10.\r \n" ); document.write( "\n" ); document.write( "**Note:**\r \n" ); document.write( "\n" ); document.write( "* This is a simplified example. In real-world scenarios, you might need to consider factors like the cost of inspection, the potential consequences of rejecting a good shipment, and the desired level of consumer confidence. \n" ); document.write( "* Statistical software or tables can provide more accurate and efficient calculations for the hypergeometric distribution.\r \n" ); document.write( "\n" ); document.write( "I hope this helps! Let me know if you have any further questions. \n" ); document.write( " \n" ); document.write( " |