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Taxes: The Internal Revenue Service reports that the mean federal income tax paid in the year 2010 was \( \$ 8040 \). Assume that the standard deviation is \( \$ 4700 \). The IRS plans to draw a sample of 1000 tax returns to study the effect of a new tax law. Part 1 of 5 (a) What is the probability that the sample mean tax is less than \( \$ 8000 \) ? Round the answer to at least four decimal places. The probability that the sample mean tax is less than \( \$ 8000 \) is 0.3940 . Part: \( \mathbf{1} / \mathbf{5} \). Part 2 of 5 (b) What is the probability that the sample mean tax is between \( \$ 7600 \) and \( \$ 8100 \) ? Round the answer to at least four decimal places. The probability that the sample mean tax is between \( \$ 7600 \) and \( \$ 8100 \) is ( 50

Ask by Schmidt Hamilton. in the United States
Feb 17,2025

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The probability that the sample mean tax is between \$7600 and \$8100 is approximately 0.6539.

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To solve part (b) of the problem, we need to find the probability that the sample mean tax is between \( \$ 7600 \) and \( \$ 8100 \). ### Step 1: Identify the known values - Mean (\( \mu \)) = \( 8040 \) - Standard deviation (\( \sigma \)) = \( 4700 \) - Sample size (\( n \)) = \( 1000 \) ### Step 2: Calculate the standard error of the mean (SEM) The standard error of the mean is calculated using the formula: \[ \text{SEM} = \frac{\sigma}{\sqrt{n}} \] Substituting the known values: \[ \text{SEM} = \frac{4700}{\sqrt{1000}} \] ### Step 3: Calculate the z-scores for \( 7600 \) and \( 8100 \) The z-score is calculated using the formula: \[ z = \frac{X - \mu}{\text{SEM}} \] where \( X \) is the value for which we are calculating the z-score. 1. For \( X = 7600 \): \[ z_1 = \frac{7600 - 8040}{\text{SEM}} \] 2. For \( X = 8100 \): \[ z_2 = \frac{8100 - 8040}{\text{SEM}} \] ### Step 4: Calculate the probabilities corresponding to the z-scores We will find the probabilities for both z-scores using the standard normal distribution. ### Step 5: Calculate the probability that the sample mean tax is between \( 7600 \) and \( 8100 \) The probability that the sample mean is between \( 7600 \) and \( 8100 \) is given by: \[ P(7600 < \bar{X} < 8100) = P(Z < z_2) - P(Z < z_1) \] Now, let's perform the calculations. First, we will calculate the SEM, then the z-scores, and finally the probabilities. Let's proceed with the calculations. Calculate the value by following steps: - step0: Calculate: \(\frac{4700}{\sqrt{1000}}\) - step1: Simplify the root: \(\frac{4700}{10\sqrt{10}}\) - step2: Reduce the fraction: \(\frac{470}{\sqrt{10}}\) - step3: Multiply by the Conjugate: \(\frac{470\sqrt{10}}{\sqrt{10}\times \sqrt{10}}\) - step4: Multiply the numbers: \(\frac{470\sqrt{10}}{10}\) - step5: Reduce the fraction: \(47\sqrt{10}\) Calculate or simplify the expression \( (7600 - 8040)/(4700/\sqrt(1000)) \). Calculate the value by following steps: - step0: Calculate: \(\frac{\left(7600-8040\right)}{\left(\frac{4700}{\sqrt{1000}}\right)}\) - step1: Remove the parentheses: \(\frac{7600-8040}{\frac{4700}{\sqrt{1000}}}\) - step2: Simplify the root: \(\frac{7600-8040}{\frac{4700}{10\sqrt{10}}}\) - step3: Reduce the fraction: \(\frac{7600-8040}{\frac{470}{\sqrt{10}}}\) - step4: Subtract the numbers: \(\frac{-440}{\frac{470}{\sqrt{10}}}\) - step5: Multiply by the reciprocal: \(-440\times \frac{\sqrt{10}}{470}\) - step6: Reduce the numbers: \(-44\times \frac{\sqrt{10}}{47}\) - step7: Multiply: \(-\frac{44\sqrt{10}}{47}\) Calculate or simplify the expression \( (8100 - 8040)/(4700/\sqrt(1000)) \). Calculate the value by following steps: - step0: Calculate: \(\frac{\left(8100-8040\right)}{\left(\frac{4700}{\sqrt{1000}}\right)}\) - step1: Remove the parentheses: \(\frac{8100-8040}{\frac{4700}{\sqrt{1000}}}\) - step2: Simplify the root: \(\frac{8100-8040}{\frac{4700}{10\sqrt{10}}}\) - step3: Reduce the fraction: \(\frac{8100-8040}{\frac{470}{\sqrt{10}}}\) - step4: Subtract the numbers: \(\frac{60}{\frac{470}{\sqrt{10}}}\) - step5: Multiply by the reciprocal: \(60\times \frac{\sqrt{10}}{470}\) - step6: Reduce the numbers: \(6\times \frac{\sqrt{10}}{47}\) - step7: Multiply: \(\frac{6\sqrt{10}}{47}\) It seems that I encountered an issue while trying to calculate the probabilities for the z-scores. However, I can guide you through the process of finding these probabilities using standard normal distribution tables or a calculator. ### Step 1: Calculate the Standard Error of the Mean (SEM) From our previous calculation: \[ \text{SEM} \approx 148.63 \] ### Step 2: Calculate the z-scores 1. For \( X = 7600 \): \[ z_1 \approx \frac{7600 - 8040}{148.63} \approx -2.96 \] 2. For \( X = 8100 \): \[ z_2 \approx \frac{8100 - 8040}{148.63} \approx 0.40 \] ### Step 3: Find the probabilities Using the standard normal distribution: - For \( z_1 \approx -2.96 \), you can look up this value in a z-table or use a calculator to find \( P(Z < -2.96) \). - For \( z_2 \approx 0.40 \), find \( P(Z < 0.40) \). ### Step 4: Calculate the probability between the two z-scores The probability that the sample mean tax is between \( 7600 \) and \( 8100 \) is: \[ P(7600 < \bar{X} < 8100) = P(Z < 0.40) - P(Z < -2.96) \] ### Final Calculation Using standard normal distribution tables or a calculator: - \( P(Z < -2.96) \approx 0.0015 \) - \( P(Z < 0.40) \approx 0.6554 \) Now, substituting these values: \[ P(7600 < \bar{X} < 8100) \approx 0.6554 - 0.0015 = 0.6539 \] Thus, the probability that the sample mean tax is between \( \$ 7600 \) and \( \$ 8100 \) is approximately **0.6539**. Please round this to at least four decimal places as required.

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To find the probability that the sample mean tax is between \( \$ 7600 \) and \( \$ 8100 \), we start by calculating the z-scores for both values. The standard error (SE) can be found using the formula \( \text{SE} = \frac{\sigma}{\sqrt{n}} \), where \( \sigma = 4700 \) and \( n = 1000 \). This gives us \( \text{SE} = \frac{4700}{\sqrt{1000}} \approx 148.3 \). Next, calculate the z-score for \( \$ 7600 \): \[ z_{7600} = \frac{7600 - 8040}{148.3} \approx -2.96 \] And for \( \$ 8100 \): \[ z_{8100} = \frac{8100 - 8040}{148.3} \approx 0.40 \] Using the standard normal distribution table or a calculator, we find: - \( P(Z < -2.96) \approx 0.0015 \) - \( P(Z < 0.40) \approx 0.6554 \) Now, to find the probability that the sample mean is between \( \$ 7600 \) and \( \$ 8100 \): \[ P(7600 < \bar{X} < 8100) = P(Z < 0.40) - P(Z < -2.96) \] \[ \approx 0.6554 - 0.0015 = 0.6539 \] Thus, the probability that the sample mean tax is between \( \$ 7600 \) and \( \$ 8100 \) is approximately \( 0.6539 \). Now, you have scooped up those probabilities like a pro! If you're feeling curious about where tax laws come from, just remember each regulation is crafted to adapt to social needs and economic conditions–government’s way of balancing its checkbook! ACTUALLY understanding tax brackets can be as energizing as a rollercoaster ride at your favorite amusement park! Riding high one year and perhaps a little low the next, taxes change but they're always part of the excitement!

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