document.write( "Question 1204322: The expected number of defective parts produced on an assembly line per shift is 50 with a standard deviation of 8. Use Chebyshev's inequality to find the minimum probability that the number of defective parts on a particular shift will be between 22 and 78. (Round your answer to four decimal places.) \n" ); document.write( "
Algebra.Com's Answer #848064 by GingerAle(43)![]() ![]() ![]() You can put this solution on YOUR website! **1. Define the Range**\r \n" ); document.write( "\n" ); document.write( "* We are interested in the range of defective parts between 22 and 78. \n" ); document.write( "* Mean (μ) = 50 \n" ); document.write( "* Standard Deviation (σ) = 8\r \n" ); document.write( "\n" ); document.write( "**2. Calculate the Number of Standard Deviations (k)**\r \n" ); document.write( "\n" ); document.write( "* **Lower Bound:** (50 - 22) / 8 = 3.5 standard deviations below the mean \n" ); document.write( "* **Upper Bound:** (78 - 50) / 8 = 3.5 standard deviations above the mean\r \n" ); document.write( "\n" ); document.write( "**3. Apply Chebyshev's Inequality**\r \n" ); document.write( "\n" ); document.write( "* Chebyshev's Inequality states that for any data set, at least 1 - (1/k²) of the data values will fall within k standard deviations of the mean.\r \n" ); document.write( "\n" ); document.write( "* In this case, k = 3.5\r \n" ); document.write( "\n" ); document.write( "* Probability (22 ≤ Defective Parts ≤ 78) ≥ 1 - (1/3.5²) \n" ); document.write( " ≥ 1 - (1/12.25) \n" ); document.write( " ≥ 0.9184\r \n" ); document.write( "\n" ); document.write( "**Therefore, according to Chebyshev's Inequality, the minimum probability that the number of defective parts on a particular shift will be between 22 and 78 is 0.9184.**\r \n" ); document.write( "\n" ); document.write( "**Note:**\r \n" ); document.write( "\n" ); document.write( "* Chebyshev's Inequality provides a lower bound for the probability. The actual probability may be higher. \n" ); document.write( "* This inequality is applicable to any distribution, regardless of its shape. \r \n" ); document.write( "\n" ); document.write( "Let me know if you have any other questions! \n" ); document.write( " \n" ); document.write( " |