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Let x Represent the Number of Minutes (Normal Distribution)

Let x represent the number of minutes needed to finish a quiz; if completion time is normally distributed, find key probabilities and a cutoff time using standardization.

Subject: Statistics Chapter: Continuous Random Variables and the Normal Distribution Topic: Standardizing a Normal Distribution Answer included
let x represent the number of minutes normal distribution z-score standardizing standard normal distribution percentile cumulative probability area under the curve
Accepted answer Answer included

Problem

Given keyword: “let x represent the number of minutes”. Interpret this as a quantitative random variable for time.

Let \(X\) represent the number of minutes required for a student to finish a short statistics quiz. Assume completion time is normally distributed with mean \(\mu=18\) minutes and standard deviation \(\sigma=3\) minutes.

  • (a) Find \(P(X \le 20)\).
  • (b) Find \(P(15 < X < 22)\).
  • (c) Find the time \(t\) such that only \(10\%\) of students take longer than \(t\).

Key idea: standardizing a normal distribution

Any value \(x\) (in minutes) can be converted to a standard normal value \(z\) using:

\[ z=\frac{x-\mu}{\sigma} \]

Then probabilities about \(X\) become probabilities about \(Z\), where \(Z\) follows the standard normal distribution.

18 μ 15 22 Shaded: P(15<X<22) Time (minutes)
The normal curve is centered at \(\mu=18\) minutes; the shaded region shows the probability that a student finishes between 15 and 22 minutes.

Solution

(a) Compute \(P(X \le 20)\)

Standardize \(x=20\): \[ z=\frac{20-18}{3}=\frac{2}{3}=0.6667 \]

So \(P(X \le 20)=P(Z \le 0.6667)\). Using the standard normal cumulative probability, \[ P(Z \le 0.6667)\approx 0.7475 \]

Answer (a): \(P(X \le 20)\approx 0.7475\).

(b) Compute \(P(15 < X < 22)\)

Standardize both bounds: \[ z_{15}=\frac{15-18}{3}=\frac{-3}{3}=-1 \] \[ z_{22}=\frac{22-18}{3}=\frac{4}{3}=1.3333 \]

Convert to a standard normal difference: \[ P(15

Using standard normal cumulative probabilities: \[ P(Z<1.3333)\approx 0.9088,\quad P(Z<-1)\approx 0.1587 \] \[ P(15

Answer (b): \(P(15

(c) Find \(t\) such that \(P(X>t)=0.10\)

The condition \(P(X>t)=0.10\) is equivalent to \(P(X\le t)=0.90\). Let \(z_{0.90}\) be the \(90\)th percentile of the standard normal distribution: \[ P(Z\le z_{0.90})=0.90,\quad z_{0.90}\approx 1.2816 \]

Convert back to minutes: \[ t=\mu+z_{0.90}\cdot\sigma=18+1.2816\cdot 3=21.8448 \]

Answer (c): \(t\approx 21.84\) minutes (about \(21.85\) minutes).

Summary table

Part Event in minutes Standardized form Approximate value
(a) \(X \le 20\) \(Z \le 0.6667\) \(0.7475\)
(b) \(15 < X < 22\) \(-1 < Z < 1.3333\) \(0.7501\)
(c) \(P(X>t)=0.10\) \(t=18+z_{0.90}\cdot 3\) \(t\approx 21.85\)

Interpretation

  • \(P(X\le 20)\approx 0.7475\): about \(74.75\%\) finish within 20 minutes.
  • \(P(15<X<22)\approx 0.7501\): about \(75.01\%\) finish between 15 and 22 minutes.
  • \(t\approx 21.85\): only about \(10\%\) take longer than roughly 21.85 minutes.
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