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```Chapter 5
Continuous Random
Variables
Figure SIA5.1 Target placement on gun
range
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5.1
Continuous Probability Distributions
Figure 5.1 A probability f(x) for a continuous
random variable x
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Definition
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Figure 5.2 Density Function for Friction
Coefficient, Example 5.1
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5.2
The Uniform Distribution
Figure 5.3 The uniform probability
distribution
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Definition
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Figure 5.4 Distribution for x in Example 5.2
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Figure 5.5 Probability that car breaks down
within 1.5 months of purchase
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5.3
The Normal Distribution
Figure 5.6 A normal probability distribution
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Figure 5.7 Several normal distributions with
different means and Standard deviations
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Procedure
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Figure 5.8 Several normal distributions:
m = 0, s = 1
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Definition
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Table 5.1
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Figure 5.9 Areas under the standard normal
curve for Example 5.3
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Figure 5.10 Finding z =1.33 in the standard
normal table, Example 5.3
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Figure 5.11 Areas under the standard
normal curve for Example 5.4
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Figure 5.12 Areas under the standard
normal curve for Example 5.5
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Figure 5.13 Areas under the standard
normal curve for Example 5.6
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Definition
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Figure 5.14 Areas under the normal curve
for Example 5.7
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Procedure
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Figure 5.15 Area under the normal curve for
Example 5.8
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Figure 5.16 Area under the standard normal
curve for Example 5.9
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Figure 5.17 Areas under the standard
normal curve for Example 5.10
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Figure 5.18 Area under the normal curve for
Example 5.11
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Figure SIA5.2 MINITAB worksheet with
cumulative normal probabilities
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5.4
Descriptive Methods for Assessing
Normality
Procedure
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Definition
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Table 5.2
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Figure 5.19a MINITAB histogram for gas
mileage data
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Figure 5.19b MINITAB Descriptive statistics
for gas mileage data
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Figure 5.19c SPSS normal probability plot
for gas mileage data
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Table 5.3
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Table SIA5.1
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Figure SIA5.3a MINITAB histogram for the
horizontal hit measurements when s = 1
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Figure SIA5.3b MINITAB histogram for the
horizontal hit measurements when s = 2
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Figure SIA5.3c MINITAB histogram for the
horizontal hit measurements when s = 4
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5.5
Approximating a Binomial Distribution with
a Normal Distribution (Optional)
Figure 5.20 Binomial distribution for n = 20,
p = .6 and normal distribution with m = 12,
s = 2.2
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Figure 5.21 Rule of thumb for normal
approximation to binomial probabilities
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Figure 5.22 Normal approximation to the
binomial distribution with n = 200, p = .06
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Figure 5.23 Standard normal distribution
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Procedure
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5.6
The Exponential Distribution (Optional)
Definition
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Figure 5.25 Exponential distributions
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Procedure
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Figure 5.27 Area to the right of a = 5 for
Example 5.14
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