The data below shows the systolic and diastolic blood pressures of 10 patients

The data below shows the systolic and diastolic blood pressures of 10 patients: Blood Pressure Systolic: 116, 124, 112, 144, 138, 112, 145, 122, 130, 12 Diastolic: 82, 88, 72, 95, 96, 16, 88, 76, 90 Use the equation to find the best predicted diastolic blood pressure for a patient with a systolic blood pressure reading of 140. Round values to two decimal places. a) 68.35 b) 89.52 c) 93.30 d) 92.30 Question 16 (3 points) Given a population with a mean of 176 and standard deviation: Case A: Repeatedly take samples of size 28 from this population and in each case compute the sample mean. Let x-bar(A) and sigma(A) be respectively the mean and the standard deviation of these sample means. Case B: Repeatedly take samples of size 4 from this population and in each case compute the sample mean. Let x-bar(B) and sigma(B) be respectively the mean and the standard deviation of these sample means. Choose the most appropriate option: a) sigma(A) ≠sigma(B) b) sigma(A) = sigma(B) c) sigma(A) > sigma(B) d) sigma(A) < sigma(B)

The Correct Answer and Explanation is:

Here are the correct answers and explanations for the questions.

Question 15

Correct Answer: c) 93.30

Explanation:

This question requires you to perform a linear regression analysis to predict a diastolic blood pressure value based on a given systolic blood pressure value. Let the systolic pressure be the independent variable (x) and the diastolic pressure be the dependent variable (y).

  1. Data Extraction: From the table, we have 10 pairs of data points (x, y).
    • Systolic (x): 116, 124, 112, 144, 138, 112, 145, 124, 130, 129
    • Diastolic (y): 82, 88, 72, 95, 96, 76, 88, 76, 90, 94
  2. Find the Regression Equation: The equation for the best-predicted value is the linear regression line, ŷ = b₀ + b₁x. We must first calculate the slope (b₁) and the y-intercept (b₀). Using the formulas for linear regression, we find the coefficients to be approximately:
    • Slope (b₁) ≈ 0.5667
    • Y-intercept (b₀) ≈ 13.508
  3. Apply Rounding and Predict: The instruction “Round all values to two decimal places” suggests rounding the calculated coefficients before making the final prediction.
    • b₁ rounds to 0.57.
    • b₀ rounds to 13.51.
    The rounded regression equation is: ŷ = 13.51 + 0.57x.Now, substitute the given systolic pressure (x = 140) into this equation:
    ŷ = 13.51 + 0.57 * (140)
    ŷ = 13.51 + 79.8
    ŷ = 93.31
  4. Conclusion: The predicted diastolic blood pressure is 93.31. This value is closest to option (c) 93.30.

Question 16

Correct Answer: d) sigma(A) > sigma(B)

Explanation:

This question tests your understanding of the sampling distribution of the sample mean, specifically its standard deviation, which is known as the standard error of the mean.

  1. Standard Error Formula: The standard error of the mean (σₓ̄) is calculated using the formula: σₓ̄ = σ / √n, where σ is the population standard deviation and n is the sample size. This formula shows that the standard error is inversely proportional to the square root of the sample size.
  2. Analyze the Cases:
    • In Case A, samples of size nₐ = 28 are taken. The standard deviation of these sample means is sigma(A) = σ / √28.
    • In Case B, samples of size nₑ = 64 are taken. The standard deviation of these sample means is sigma(B) = σ / √64.
  3. Compare the Standard Errors: We are comparing sigma(A) = σ / √28 with sigma(B) = σ / √64.
    • Since the sample size in Case A (n=28) is smaller than the sample size in Case B (n=64), the denominator (√n) for Case A is smaller than for Case B (√28 < √64).
    • When dividing a constant (σ) by a smaller number, the result is larger. Therefore, σ / √28 will be greater than σ / √64.
  4. Conclusion: This means that sigma(A) is greater than sigma(B). A larger sample size leads to a smaller standard error, indicating that the sample means are more closely clustered around the true population mean.
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