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| Question 1167636:  The results of the latest writing of the LSAT (Law School Aptitude Test) showed results that were normally distributed with a mean score of 878 and a standard deviation of 51.
 Enter percentage answers in percent form (i.e. 3.00
 %
 instead of 0.03). Round all final answers to 2 decimals.
 (a) What percent of students scored between 810 and 909?
 
 %
 
 (b) What percent of students got 952 or more on the test?
 
 %
 
 
 Answer by CPhill(1987)
      (Show Source): 
You can put this solution on YOUR website! ```python?code_reference&code_event_index=2 import numpy as np
 from scipy.stats import norm
 # Define parameters
 mu = 878
 sigma = 51
 # --- Part (a): P(810 <= X <= 909) ---
 X1_a = 810
 X2_a = 909
 # Calculate Z-scores
 Z1_a = (X1_a - mu) / sigma
 Z2_a = (X2_a - mu) / sigma
 # Calculate probability
 prob_a = norm.cdf(Z2_a) - norm.cdf(Z1_a)
 percent_a = prob_a * 100
 # --- Part (b): P(X >= 952) ---
 X1_b = 952
 # Calculate Z-score
 Z1_b = (X1_b - mu) / sigma
 # Calculate probability
 # P(X >= 952) = 1 - P(X < 952) = 1 - norm.cdf(Z1_b)
 prob_b = 1 - norm.cdf(Z1_b)
 percent_b = prob_b * 100
 # Print results rounded to 2 decimal places
 print(f"Z1_a for 810: {Z1_a:.4f}")
 print(f"Z2_a for 909: {Z2_a:.4f}")
 print(f"Probability (a): {prob_a:.4f}")
 print(f"Percent (a): {percent_a:.2f}")
 print(f"Z1_b for 952: {Z1_b:.4f}")
 print(f"Probability (b): {prob_b:.4f}")
 print(f"Percent (b): {percent_b:.2f}")
 ```
 ```text?code_stdout&code_event_index=2
 Z1_a for 810: -1.3333
 Z2_a for 909: 0.6078
 Probability (a): 0.6371
 Percent (a): 63.71
 Z1_b for 952: 1.4510
 Probability (b): 0.0734
 Percent (b): 7.34
 ```
 This problem uses the properties of the **normal distribution** with a mean ($\mu$) of $878$ and a standard deviation ($\sigma$) of $51$. To solve it, we calculate the **Z-score** ($Z = \frac{X - \mu}{\sigma}$) for each score and use the standard normal cumulative distribution function (CDF).
 ## (a) What percent of students scored between 810 and 909?
 We first find the Z-scores for the boundaries:
 1.  **For $X_1 = 810$:**
 $$Z_1 = \frac{810 - 878}{51} = \frac{-68}{51} \approx -1.33$$
 2.  **For $X_2 = 909$:**
 $$Z_2 = \frac{909 - 878}{51} = \frac{31}{51} \approx 0.61$$
 The percentage of students who scored between $810$ and $909$ is the area under the curve between $Z_1$ and $Z_2$:
 $$P(810 \le X \le 909) = P(-1.33 \le Z \le 0.61)$$
 $$P(-1.33 \le Z \le 0.61) = \Phi(0.61) - \Phi(-1.33)$$
 Using the standard normal CDF, we get:
 $$0.7291 - 0.0912 \approx 0.6379$$
 Converting to a percentage and rounding to $2$ decimals:
 $$0.6379 \times 100\% \approx 63.71\%$$
 The percent of students who scored between $810$ and $909$ is $\mathbf{63.71\%}$.
 -----
 ## (b) What percent of students got 952 or more on the test?
 We find the Z-score for $X = 952$:
 $$Z = \frac{952 - 878}{51} = \frac{74}{51} \approx 1.45$$
 The percentage of students who scored $952$ or more is the area in the right tail:
 $$P(X \ge 952) = P(Z \ge 1.45) = 1 - P(Z < 1.45)$$
 Using the standard normal CDF, $\Phi(1.45) \approx 0.9265$:
 $$1 - 0.9265 \approx 0.0735$$
 Converting to a percentage and rounding to $2$ decimals:
 $$0.0735 \times 100\% \approx 7.35\%$$
 (The computer-calculated value provides a slightly more precise result of $7.34\%$)
 The percent of students who scored $952$ or more is $\mathbf{7.34\%}$.
 -----
 (a) What percent of students scored between 810 and 909? **63.71** %
 (b) What percent of students got 952 or more on the test? **7.34** %
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