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 6.1.50
Textbook Question
Distributions In a continuous uniform distribution,

a. Find the mean and standard deviation for the distribution of the waiting times represented in Figure 6-2, which accompanies Exercises 5–8.

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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. This means that any value between the minimum and maximum is equally probable, leading to a flat probability density function. The distribution is defined by its two parameters: the minimum and maximum values, which determine the range of possible outcomes.
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Mean of a Uniform Distribution
The mean (μ) of a continuous uniform distribution is calculated as the average of the minimum and maximum values. It represents the central point of the distribution and is given by the formula μ = (minimum + maximum) / 2. This value indicates where the center of the distribution lies, providing insight into the expected value of a random variable drawn from this distribution.
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Standard Deviation of a Uniform Distribution
The standard deviation (σ) of a continuous uniform distribution measures the spread of the distribution around the mean. It is calculated using the formula σ = range / √12, where the range is the difference between the maximum and minimum values. A larger standard deviation indicates a wider spread of values, while a smaller standard deviation suggests that the values are closer to the mean.
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