Table of contents
- 1. Intro to Stats and Collecting Data24m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically53m
- 4. Probability1h 29m
- 5. Binomial Distribution & Discrete Random Variables1h 16m
- 6. Normal Distribution and Continuous Random Variables58m
- 7. Sampling Distributions & Confidence Intervals: Mean1h 3m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 5m
- 9. Hypothesis Testing for One Sample1h 1m
- 10. Hypothesis Testing for Two Samples2h 8m
- 11. Correlation48m
6. Normal Distribution and Continuous Random Variables
Probabilities & Z-Scores w/ Graphing Calculator
Problem 6.1.5
Textbook Question
Continuous Uniform Distribution. In Exercises 5–8, refer to the continuous uniform distribution depicted in Figure 6-2 and described in Example 1. Assume that a passenger is randomly selected, and find the probability that the waiting time is within the given range.

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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Continuous Uniform Distribution
A continuous uniform distribution is a probability distribution where all outcomes are equally likely within a specified range. The probability density function (PDF) is constant across this interval, meaning that the likelihood of any specific value is the same. In the context of waiting times, this distribution can be used to model scenarios where the waiting time is uniformly distributed between a minimum and maximum value.
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Probability Density Function (PDF)
The probability density function (PDF) describes the likelihood of a continuous random variable taking on a specific value. For a continuous uniform distribution, the PDF is a horizontal line, indicating that the probability is evenly distributed across the range. The area under the PDF curve represents the total probability, which equals 1, and the height of the line is determined by the range of values.
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Calculating Probabilities
To find the probability of a continuous random variable falling within a certain range, one must calculate the area under the PDF over that interval. For the continuous uniform distribution, this is done by multiplying the height of the PDF by the width of the interval. For example, to find the probability that the waiting time is greater than 3 minutes, one would calculate the area from 3 to the maximum value of the distribution.
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