Download - Chapter 5: z-Scores
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Chapter 5: z-Scores
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12
82
x = 76
(a)
€
μ =82
€
σ =12
X = 76 is slightly below
average
12
70
x = 76
(b)
€
μ =70
€
σ =12
X = 76 is slightly above
average
3
70
x = 76
(c)
€
μ =70
€
σ =3
X = 76 is far above average
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Definition of z-score
• A z-score specifies the precise location of each x-value within a distribution. The sign of the z-score (+ or - ) signifies whether the score is above the mean (positive) or below the mean (negative). The numerical value of the z-score specifies the distance from the mean by counting the number of standard deviations between X and µ.
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X€
σ
€
μz
-2 -1 0 +1 +2
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Example 5.2
• A distribution of exam scores has a mean (µ) of 50 and a standard deviation (σ) of 8.
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€
z = x−μσ
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σ
σ
σ = 4
60 64 68µ
X66
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Example 5.5
• A distribution has a mean of µ = 40 and a standard deviation of σ = 6.
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To get the raw score from the z-score:
€
x =
€
μ+ zσ
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If we transform every score in a distribution by assigning a z-score, new
distribution:
1. Same shape as original distribution
2. Mean for the new distribution will be zero
3. The standard deviation will be equal to 1
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X
€
σ
€
μz
-2 -1 0 +1 +2
100 110 1209080
€
μ
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A small population
0, 6, 5, 2, 3, 2 N=6
x x - µ (x - µ)2
0 0 - 3 = -3 9
6 6 - 3 = +3 9
5 5 - 3 = +2 4
2 2 - 3 = -1 1
3 3 - 3 = 0 0
2 2 - 3 = -1 1
€
(x −μ )2 = SS∑
€
=24
€
μ = x∑N
€
=186
€
=3€
σ = SSN
€
= (x −μ )2∑6
€
= 246
€
= 4
€
=2
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2
1
0 1 2 3 4 5 6µ
X
freq
uenc
y
(a)
2
1
-1.5 -1.0 -0.5 0 +0.5 +1.0 +1.5µ
z
freq
uenc
y
(b)
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Let’s transform every raw score into a z-score using:
€
z =x −μσ
x = 0
x = 6
x = 5
x = 2
x = 3
x = 2
€
z =0 − 3
2
€
z =6 − 3
2
€
z =5 − 3
2
€
z =2 − 3
2
€
z =3− 3
2
= -1.5
= +1.5
= +1.0
= -0.5
= 0
= -0.5
€
z =2 − 3
2
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Mean of z-score distribution :
€
μz =z∑N
€
=(−1.5)+ (1.5)+ (1.0)+ (−0.5)+ (0)+ (−0.5)6
€
=0
Standard deviation:
€
σ z =SSzN
€
=(x −μ z )
2∑
N
z z - µz (z - µz)2
-1.5 -1.5 - 0 = -1.5 2.25
+1.5 +1.5 - 0 = +1.5 2.25
+1.0 +1.0 - 0 = +1.0 1.00
-0.5 -0.5 - 0 = -0.5 0.25
0 0 - 0 = 0 0
-0.5 -0.5 - 0 = -0.5 0.25
€
σ = SSN
€
= 66
€
= 1 =1
€
6.00 = (z−μ z )2∑
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10
50µ
X = 60
X
Psychology
4
48µ
X = 56
X
Biology
52
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Converting Distributions ofScores
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14
57µ
JoeX = 64
z = +0.50
X
Original Distribution
10
50µ
X
Standardized Distribution
MariaX = 43
z = -1.00
MariaX = 40
z = -1.00
JoeX = 55
z = +0.50
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Correlating Two Distributionsof Scores with z-scores
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= 4
µ = 68
Person AHeight = 72 inches
Distribution of adult heights (in inches)
= 16
µ = 140
Person BWeight = 156 pounds
Distribution of adult weights (in pounds)