Chapter 7 Continuous Distributions. Continuous random variables Are numerical variables whose values...
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![Page 1: Chapter 7 Continuous Distributions. Continuous random variables Are numerical variables whose values fall within a range or interval Are measurements.](https://reader035.fdocuments.net/reader035/viewer/2022062304/56649e495503460f94b3be34/html5/thumbnails/1.jpg)
Chapter 7Chapter 7Continuous
Distributions
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Continuous random Continuous random variablesvariables
•Are numerical variables whose values fall within a range or interval
•Are measurements•Can be described by density curves
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Density curvesDensity curves• Is always on or aboveon or above the
horizontal axis• Has an area exactly equal to oneequal to one
underneath it• Often describes an overall
distribution• Describe what proportionsproportions of the
observations fall within each range of values
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Unusual density Unusual density curvescurves
•Can be any shape•Are generic continuous distributions
•Probabilities are calculated by finding the finding the area under the curvearea under the curve
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1 2 3 4 5
.5
.25
P(X < 2) =
25.
225.2
How do you find the area of a triangle?
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1 2 3 4 5
.5
.25
P(X = 2) =
0
P(X < 2) =
.25
What is the area of a line
segment?
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In continuous distributions, P(P(XX < 2) & P( < 2) & P(XX << 2)2) are the same answer.
Hmmmm…
Is this different than
discrete distributions?
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1 2 3 4 5
.5
.25
P(X > 3) =
P(1 < X < 3) =
Shape is a trapezoid –
How long are the bases?
2
21 hbbArea
.5(.375+.5)(1)=.4375
.5(.125+.375)(2) =.5
b2 = .375
b1 = .5
h = 1
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1 2 3 4
0.25
0.50 P(X > 1) =.75
.5(2)(.25) = .25
(2)(.25) = .5
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1 2 3 4
0.25
0.50P(0.5 < X < 1.5) =
.28125
.5(.25+.375)(.5) = .15625
(.5)(.25) = .125
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Special Continuous Distributions
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Uniform DistributionUniform Distribution• Is a continuous distribution that is
evenly (or uniformly) distributed• Has a density curve in the shape
of a rectangle• Probabilities are calculated by
finding the area under the curve
12
22
2 ab
ba
x
x
Where: a & b are the endpoints of the uniform distribution
How do you find the area of a rectangle?
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4.98 5.044.92
The Citrus Sugar Company packs sugar in bags labeled 5 pounds. However, the packaging isn’t perfect and the actual weights are uniformly distributed with a mean of 4.98 pounds and a range of .12 pounds.
a)Construct the uniform distribution above.
How long is this rectangle?
What is the height of this rectangle?
What shape does a uniform distribution
have?
1/.12
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• What is the probability that a randomly selected bag will weigh more than 4.97 pounds?
4.98 5.044.92
1/.12
P(X > 4.97) =
.07(1/.12) = .5833What is the length of the shaded
region?
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• Find the probability that a randomly selected bag weighs between 4.93 and 5.03 pounds.
4.98 5.044.92
1/.12
P(4.93<X<5.03) =
.1(1/.12) = .8333What is the length of the shaded
region?
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The time it takes for students to The time it takes for students to drive to school is evenly distributed drive to school is evenly distributed with a minimum of 5 minutes and a with a minimum of 5 minutes and a range of 35 minutes.range of 35 minutes.
a)Draw the distribution
5
Where should the rectangle
end?
40
What is the height of the rectangle?
1/35
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b) What is the probability that it takes less than 20 minutes to drive to school?
5 40
1/35
P(X < 20) =
(15)(1/35) = .4286
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c) What is the mean and standard deviation of this distribution?
= (5 + 40)/2 = 22.5
= (40 - 5)2/12 = 102.083
= 10.104
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Normal Normal DistributionsDistributions
• Symmetrical bell-shaped (unimodal) density curve
• AboveAbove the horizontal axis• N(, )• The transition points occur at + • Probability is calculated by finding the area area
under the curveunder the curve• As increasesincreases, the curve flattens &
spreads out• As decreasesdecreases, the curve gets
taller and thinner
How is this done
mathematically?
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A
B
Do these two normal curves have the same mean? If so, what is it?
Which normal curve has a standard deviation of 3?
Which normal curve has a standard deviation of 1?
6
YESYES
BB
AA
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Empirical RuleEmpirical Rule•Approximately 68%68% of the
observations fall within of •Approximately 95%95% of the
observations fall within 2 of •Approximately 99.7%99.7% of the
observations fall within 3 of
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Suppose that the height of male students at PWSH is normally distributed with a mean of 71 inches and standard deviation of 2.5 inches. What is the probability that the height of a randomly selected male student is more than 73.5 inches?P(X > 73.5) = 0.16
71
68%
1 - .68 = .32
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Standard Normal Standard Normal Density CurvesDensity Curves
Always has = 0 & = 1
To standardize:
x
zMust have
this memorize
d!
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Strategies for finding Strategies for finding probabilities or proportions in probabilities or proportions in
normal distributionsnormal distributions
1.State the probability statement
2.Draw a picture3.Calculate the z-score4.Look up the probability
(proportion) in the table
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The lifetime of a certain type of battery is normally distributed with a mean of 200 hours and a standard deviation of 15 hours. What proportion of these batteries can be expected to last less than 220 hours?P(X < 220) =
33.115
200220
z
.9082
Write the probability statement
Draw & shade the
curve
Calculate z-score
Look up z-score in
table
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The lifetime of a certain type of battery is normally distributed with a mean of 200 hours and a standard deviation of 15 hours. What proportion of these batteries can be expected to last more than 220 hours?P(X>220) =
33.115
200220
z
1 - .9082 = .0918
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The lifetime of a certain type of battery is normally distributed with a mean of 200 hours and a standard deviation of 15 hours. How long must a battery last to be in the top 5%?P(X > ?) = .05
675.22415
200645.1
x
x .95.05
Look up in table 0.95 to find z- score
1.645
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The heights of the female students at PWSH are normally distributed with a mean of 65 inches. What is the standard deviation of this distribution if 18.5% of the female students are shorter than 63 inches?P(X < 63) = .185
6322.2
9.2
65639.
What is the z-score for the 63?
-0.9
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Will my calculator do any of this normal
stuff?• Normalpdf – use for graphing
ONLYONLY
• Normalcdf – will find probability of area from lower bound to upper bound
• Invnorm (inverse normal) – will find z-score for probability
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The lifetime of a certain type of battery is normally distributed with a mean of 200 hours and a standard deviation of 15 hours. What proportion of these batteries can be expected to last less than 220 hours?
P(X < 220) =
Normalcdf(-∞,220,200,15)=.9082
N(200,15)
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The lifetime of a certain type of battery is normally distributed with a mean of 200 hours and a standard deviation of 15 hours. What proportion of these batteries can be expected to last more than 220 hours?
P(X>220) =
Normalcdf(220,∞,200,15) = .0918
N(200,15)
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The lifetime of a certain type of battery is normally distributed with a mean of 200 hours and a standard deviation of 15 hours. How long must a battery last to be in the top 5%?P(X > ?) = .05
.95.05
Invnorm(.95,200,15)=224.675
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The heights of female teachers at PWSH are normally distributed with mean of 65.5 inches and standard deviation of 2.25 inches. The heights of male teachers are normally distributed with mean of 70 inches and standard deviation of 2.5 inches. •Describe the distribution of differences of heights (male – female) teachers.
Normal distribution with = 4.5 & = 3.3634
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• What is the probability that a randomly selected male teacher is shorter than a randomly selected female teacher?
4.5
P(X<0) =
Normalcdf(-∞,0,4.5,3.3634 = .0901
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Ways to Assess NormalityWays to Assess Normality
•Use graphs (dotplots, boxplots, or histograms)
•Normal probability (quantile) plot
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Normal Probability (Quantile) Normal Probability (Quantile) plotsplots
• The observation (x) is plotted against known normal z-scores
• If the points on the quantile plot lie close to a straight line, then the data is normally distributed
• Deviations on the quantile plot indicate nonnormal data
• Points far away from the plot indicate outliers
• Vertical stacks of points (repeated observations of the same number) is called granularity
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Consider a random sample with n = 5.To find the appropriate z-scores for a sample of size 5, divide the standard normal curve into 5 equal-area regions.
Why are these
regions not the same
width?
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Consider a random sample with n = 5.Next – find the median z-score for each region.
-1.28 0 1.28
-.524 .524
Why is the median
not in the “middle” of each region?
These would be the z-scores (from the standard normal
curve) that we would use to plot our data against.
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Let’s construct a normal probability plot. The values of the normal scores depend on the sample size n. The normal scores when n = 10 are below:
-1.539 -1.001 -0.656 -0.376 -0.123 0.123 0.376 0.656 1.001 1.539
Suppose we have the following observations of widths of contact windows in integrated circuit chips:
3.21 2.49 2.94 4.38 4.02 3.62 3.30 2.85 3.34 3.81
Sketch a scatterplot by pairing the smallest normal score
with the smallest observation from the data set & so on
1 2 3 4 5
-1
1N
orm
al S
core
s
Widths of Contact Windows
What should happen if our data
set is normally distribute
d?
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Notice that the boxplot is
approximately symmetrical and that the normal
probability plot is approximately
linear.
Notice that the boxplot is
approximately symmetrical except for the outlier and
that the normal probability plot
shows the outlier.
Notice that the boxplot is skewed left and that the
normal probability plot shows this
skewness.
![Page 41: Chapter 7 Continuous Distributions. Continuous random variables Are numerical variables whose values fall within a range or interval Are measurements.](https://reader035.fdocuments.net/reader035/viewer/2022062304/56649e495503460f94b3be34/html5/thumbnails/41.jpg)
Are these approximately normally distributed?
50 48 54 47 51 52 46 53 52 51 48 48 54 55 57 45 53 50 47 49 50 56 53 52
Both the histogram & boxplot are approximately symmetrical, so these data are approximately normal.
The normal probability plot is approximately linear, so these data are approximately normal.
What is this
called?