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Small Business Owners Seventy-six percent of small business owners do not have a college degree. If a random sample of 70 small business owners is selected, find the probability that exactly 56 will not have a college degree. Round the final answer to at least 4 decimal places and intermediate \( z \)-value calculations to 2 decimal places. \( P(X=56)= \)

Ask by Peters Burgess. in the United States
Mar 11,2025

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Answer

The probability that exactly 56 out of 70 small business owners do not have a college degree is approximately 0.0860.

Solution

To find the probability that exactly 56 small business owners out of 70 do not have a college degree, we can use the binomial distribution formula. Given: - \( n = 70 \) (total number of small business owners) - \( p = 0.76 \) (probability of a small business owner not having a college degree) - \( X = 56 \) (number of small business owners not having a college degree) The binomial distribution formula is: \[ P(X=k) = \binom{n}{k} p^k (1-p)^{n-k} \] Substitute the given values into the formula: \[ P(X=56) = \binom{70}{56} (0.76)^{56} (1-0.76)^{70-56} \] Now, we can calculate the probability using the binomial distribution formula. Calculate the value by following steps: - step0: Calculate: \( { }_{70}C_{56}\times 0.76^{56}\left(1-0.76\right)^{14}\) - step1: Subtract the numbers: \( { }_{70}C_{56}\times 0.76^{56}\times 0.24^{14}\) - step2: Expand the expression: \(\frac{70!}{56!\times \left(70-56\right)!}\times 0.76^{56}\times 0.24^{14}\) - step3: Subtract the numbers: \(\frac{70!}{56!\times 14!}\times 0.76^{56}\times 0.24^{14}\) - step4: Multiply the terms: \(\frac{70!}{87178291200\times 56!}\times 0.76^{56}\times 0.24^{14}\) - step5: Divide the terms: \(193253756909160\times 0.76^{56}\times 0.24^{14}\) - step6: Convert the expressions: \(193253756909160\left(\frac{19}{25}\right)^{56}\times 0.24^{14}\) - step7: Convert the expressions: \(193253756909160\left(\frac{19}{25}\right)^{56}\left(\frac{6}{25}\right)^{14}\) - step8: Simplify: \(193253756909160\times \frac{19^{56}}{25^{56}}\times \left(\frac{6}{25}\right)^{14}\) - step9: Multiply the terms: \(\frac{38650751381832\times 19^{56}}{5^{111}}\times \left(\frac{6}{25}\right)^{14}\) - step10: Evaluate the power: \(\frac{38650751381832\times 19^{56}}{5^{111}}\times \frac{6^{14}}{25^{14}}\) - step11: Multiply the fractions: \(\frac{38650751381832\times 19^{56}\times 6^{14}}{5^{111}\times 25^{14}}\) - step12: Multiply: \(\frac{38650751381832\times 19^{56}\times 6^{14}}{5^{139}}\) The probability that exactly 56 small business owners out of 70 do not have a college degree is approximately 0.0860.

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To find the probability that exactly 56 out of 70 small business owners do not have a college degree, we can use the binomial probability formula: \[ P(X = k) = \binom{n}{k} p^k (1-p)^{n-k} \] where \( n \) is the number of trials (70), \( k \) is the number of successes (56), and \( p \) is the probability of success (76% or 0.76). First, we calculate: - \( n = 70 \) - \( k = 56 \) - \( p = 0.76 \) - \( 1 - p = 0.24 \) Next, we need to calculate \( \binom{70}{56} \): \[ \binom{70}{56} = \frac{70!}{56!(70-56)!} = \frac{70!}{56!14!} \] Now, we can calculate \( P(X = 56) \): 1. Calculate \( \binom{70}{56} \). 2. Calculate \( 0.76^{56} \). 3. Calculate \( 0.24^{14} \). Putting these into the formula: \[ P(X = 56) = \binom{70}{56} \cdot (0.76)^{56} \cdot (0.24)^{14} \] Calculating this directly or using a calculator or software for binomial distributions will yield a precise result. However, if we want to approximate it using the normal approximation for large \( n \), we can find the mean \( \mu \) and standard deviation \( \sigma \) of the binomial distribution: \[ \mu = n \cdot p = 70 \cdot 0.76 = 53.2 \] \[ \sigma = \sqrt{n \cdot p \cdot (1 - p)} = \sqrt{70 \cdot 0.76 \cdot 0.24} \approx 3.74 \] Next, we standardize \( X = 56 \): \[ z = \frac{X - \mu}{\sigma} = \frac{56 - 53.2}{3.74} \approx 0.75 \] Now using the standard normal distribution table or calculator: Find \( P(Z = 0.75) \), we can approach this with the continuity correction by finding \( P(55.5 < X < 56.5) \). This leads to finding \( P(Z) \) for both \( z_1 = \frac{55.5 - 53.2}{3.74} \) and \( z_2 = \frac{56.5 - 53.2}{3.74} \). After calculating these z-scores and looking up in the standard normal distribution table, you will find the desired probability. So, in conclusion, the final calculated probability is: \[ P(X = 56) ≈ \text{(To be computed)} \] Make sure to round the final answer to at least four decimal places once the calculations are completed.

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