Transcript Document
Chapter 3
The Normal Distributions
BPS - 3rd Ed.
Chapter 3
1
Density Curves
Here is a histogram of
vocabulary scores of
947 seventh graders
The smooth curve
drawn over the
histogram is a
mathematical model for
the distribution.
The mathematical
model is called the
density function.
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2
Density Curves
The areas of the
shaded bars in this
histogram represent the
proportion of scores in
the observed data that
are less than or equal to
6.0.
This proportion is equal
to 0.303.
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3
Areas under density curves
The
scale of the Y-axis
of the density curve is
adjusted so the total
area under the curve is 1
The area under the
curve to the left of 6.0 is
shaded, and is equal to
0.293
This similar to the
areas of the shaded bars
in the prior slide!
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Density Curves
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Chapter 3
5
Density Curves
There
are many types of density curves
We
are going to focus on a family of
curves called Normal curves
Normal
curves are
– bell-shaped
– not too steep, not too fat
– defined means & standard deviations
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Normal Density Curves
The
mean and standard deviation
computed from actual observations
(data) are denoted by x and s,
respectively.
The
mean and standard deviation of the
distribution represented by the density
curve are denoted by µ (“mu”) and
(“sigma”), respectively.
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Chapter 3
7
Bell-Shaped Curve:
The Normal Distribution
standard deviation
mean
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8
The Normal Distribution
Mean µ defines the center of the curve
Standard deviation defines the spread
Notation is N(µ,).
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Practice Drawing Curves!
Symmetrical around μ
Infections points (change in slope, blue arrows) at ± σ
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10
68-95-99.7 Rule for
Any Normal Curve
68%
of the observations fall within one
standard deviation of the mean
95% of the observations fall within two
standard deviations of the mean
99.7% of the observations fall within
three standard deviations of the mean
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68-95-99.7 Rule for
Any Normal Curve
68%
-
95%
µ +
-2
µ
+2
99.7%
-3
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µ
Chapter 3
+3
12
68-95-99.7 Rule for
Any Normal Curve
BPS - 3rd Ed.
Chapter 3
13
Men’s Height Example (NHANES, 1980)
Suppose
heights of men follow a Normal
distribution with mean = 70.0 inches and
standard deviation = 2.8 inches
Shorthand:
X ~ N(70, 2.8)
X the variable
~ “distributed as”
N(μ, σ) Normal with mean μ and standard
deviation σ
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Men’s Height Example 68-95-99.7 rule
If X~N(70, 2.8)
68% between µ = 70.0 2.8 = 67.2 to 72.8
95% between µ 2 = 70.0 2(2.8) = 70.0 5.6 =
64.4 to 75.6 inches
99.7% between µ 3 = 70.0 3(2.8) = 70.0
8.4 = 61.6 and 78.4 inches
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NHANES (1980) Height Example
What proportion of men are less than 72.8 inches tall?
(Note: 72.8 is one σ above μ on this distribution)
68%
16%
?
-1
+1
84%
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(by 68-95-99.7 Rule)
70
Chapter 3
72.8
(height)
16
NHANES Height Example
What proportion of men are less than 68
inches tall?
?
68 70
(height values)
How many standard deviations is 68 from 70?
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Chapter 3
17
Standard Normal (Z) Distribution
The
Standard Normal distribution has mean 0
and standard deviation 1
We call this a Z distribution: Z~N(0,1)
Any
Normal variable x can be turned into a Z
variable (standardized) by subtracting μ and
dividing by σ:
z
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x
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Standardized Scores
How
many standard deviations is 68
from μ on X~N(70,2.8)?
z
= (x – μ) / σ
= (68 70) / 2.8
= 0.71
The
value 68 is 0.71 standard
deviations below the mean 70
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Chapter 3
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Men’s Height Example (NHANES, 1980)
What
proportion of men are less than
68 inches tall?
?
68 70
-0.71
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0
(height values)
(standardized values)
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Table A in text:
Standard Normal Table
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Table A:
Standard Normal Probabilities
z
.00
.01
.02
0.8
.2119
.2090
.2061
0.7
.2420
.2389
.2358
0.6
.2743
.2709
.2676
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Chapter 3
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Men’s Height Example (NHANES, 1980)
What
proportion of men are less than
68 inches tall?
.2389
68 70
-0.71
BPS - 3rd Ed.
0
(height values)
(standardized values)
Chapter 3
23
Men’s Height Example (NHANES, 1980)
What proportion of men are greater than 68
inches tall?
Area under curve sums to 1, so Pr(X > x) = 1
– Pr(X < x), as shown below:
1.2389 =
.2389
.7611
68 70
-0.71
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0
(height values)
(standardized values)
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Men’s Height Example (NHANES, 1980)
How
tall must a man be to place in the
lower 10% for men aged 18 to 24?
.10
? 70
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(height values)
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Table A:
Standard Normal Table
Use
Table A
Look
up the closest proportion in the table
Find
corresponding standardized score
Solve
for X (“un-standardize score”)
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Table A:
Standard Normal Proportion
z
.07
1.3
.0853
1.2
.1020
1.1
.1210
.08
.0838
.1003
.1190
.09
.0823
.0985
.1170
Pr(Z < -1.28) = .1003
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Men’s Height Example (NHANES, 1980)
How
tall must a man be to place in the
lower 10% for men aged 18 to 24?
.10
? 70
-1.28
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0
(height values)
(standardized values)
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28
Observed Value for a
Standardized Score
“Unstandardize”
z-score to find
associated x :
z
x
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x z
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Observed Value for a
Standardized Score
x
= μ + zσ
= 70 + (1.28 )(2.8)
= 70 + (3.58)
= 66.42
A man
would have to be approximately
66.42 inches tall or less to place in the
lower 10% of the population
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