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 
Mirasol S. Madrid III-9 BS Psychology
Also called as z scores
Measures the difference
between the raw score and the
mean of the distribution using
standard deviation of the
distribution as a unit of
Reflects how many
standard deviations above
or below the mean a raw
score is
By itself, a raw score or X
value provides very little
information about how that
particular score compares
with other values in the
distribution.
A score of X = 53, for
example, may be a
relatively low score, or an
average score, or an
extremely high score
depending on the mean and
standard deviation for the
distribution from which the
score was obtained.
50 60 70 80403020
0 1 2 3-1-2-3
x
z
If the raw score is
transformed into a z-score,
however, the value of the z-
score tells exactly where the
score is located relative to
all the other scores in the
distribution.
𝑧 =
(𝑥 − 𝑥)
𝑠
Where:
Z = standard score/z-score
X = Raw Score
𝒙 = Mean
S = Standard Deviation
𝑧 =
(𝑥 − 𝜇)
𝜎
Where:
Z = standard score/z-score
X = Raw Score
𝝁 = Mean
𝝈 = (sigma) Standard Deviation
Z-scores can be positive
(above the mean),
negative (below the
mean), or zero (equal to
the mean)

In a distribution of
statistic test score,
having the mean of 75
and a standard deviation
of 10, find the z score,
scoring 85
X = 85
𝑥 = 75
S = 10
1. Step 1
𝑧 =
(85 − 75)
10
2. Step 2
𝑧 =
(10)
10
z = 1
A score of 85 is one (1)
standard deviation
above the mean

Find the Z score of 60
having a mean of 75
and a standard
deviation of 10
X = 60
𝑥 = 75
S = 10
1. Step 1
𝑧 =
(55 − 75)
10
2. Step 2
𝑧 =
(−20)
10
z= -2
A score of 60 is two (2)
standard deviation
below the mean

X = 100
𝑥 = 100
S = 10
1. Step 1
𝑧 =
(100 − 100)
10
2. Step 2
𝑧 =
(0)
10
z= 0
A score of 100 is falls
on the given mean.

1. X = 58, µ = 50, σ = 10
2. X = 74, µ = 65, σ = 6
3. X = 47, µ = 50, σ = 5
4. X = 87, µ = 100, σ = 8
5. X = 22, µ = 15, σ = 5
1. z = +.8
2. z = +1.5
3. z = -.6
4. z = -1.625
5. z = +1.4

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Standard Scores

  • 1.   Mirasol S. Madrid III-9 BS Psychology
  • 2. Also called as z scores Measures the difference between the raw score and the mean of the distribution using standard deviation of the distribution as a unit of
  • 3. Reflects how many standard deviations above or below the mean a raw score is
  • 4. By itself, a raw score or X value provides very little information about how that particular score compares with other values in the distribution.
  • 5. A score of X = 53, for example, may be a relatively low score, or an average score, or an extremely high score depending on the mean and standard deviation for the distribution from which the score was obtained.
  • 6. 50 60 70 80403020 0 1 2 3-1-2-3 x z
  • 7. If the raw score is transformed into a z-score, however, the value of the z- score tells exactly where the score is located relative to all the other scores in the distribution.
  • 8. 𝑧 = (𝑥 − 𝑥) 𝑠 Where: Z = standard score/z-score X = Raw Score 𝒙 = Mean S = Standard Deviation
  • 9. 𝑧 = (𝑥 − 𝜇) 𝜎 Where: Z = standard score/z-score X = Raw Score 𝝁 = Mean 𝝈 = (sigma) Standard Deviation
  • 10. Z-scores can be positive (above the mean), negative (below the mean), or zero (equal to the mean)
  • 12. In a distribution of statistic test score, having the mean of 75 and a standard deviation of 10, find the z score, scoring 85
  • 13. X = 85 𝑥 = 75 S = 10
  • 14. 1. Step 1 𝑧 = (85 − 75) 10 2. Step 2 𝑧 = (10) 10 z = 1
  • 15. A score of 85 is one (1) standard deviation above the mean
  • 17. Find the Z score of 60 having a mean of 75 and a standard deviation of 10
  • 18. X = 60 𝑥 = 75 S = 10
  • 19. 1. Step 1 𝑧 = (55 − 75) 10 2. Step 2 𝑧 = (−20) 10 z= -2
  • 20. A score of 60 is two (2) standard deviation below the mean
  • 22. X = 100 𝑥 = 100 S = 10
  • 23. 1. Step 1 𝑧 = (100 − 100) 10 2. Step 2 𝑧 = (0) 10 z= 0
  • 24. A score of 100 is falls on the given mean.
  • 26. 1. X = 58, µ = 50, σ = 10 2. X = 74, µ = 65, σ = 6 3. X = 47, µ = 50, σ = 5 4. X = 87, µ = 100, σ = 8 5. X = 22, µ = 15, σ = 5
  • 27. 1. z = +.8 2. z = +1.5 3. z = -.6 4. z = -1.625 5. z = +1.4