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Transcript
```Interpreting
Performance Data
Expected Outcomes
Understand the terms mean, median,
mode, standard deviation
Use these terms to interpret
performance data supplied by EAU
Measures of Central Tendency
Mean … the average score
Median … the value that lies in the
middle after ranking all the scores
Mode … the most frequently occurring
score
Measures of Central Tendency
Which measure of Central
Tendency should be used?
Measures of Central Tendency
The measure you choose should give
you a good indication of the typical
score in the sample or population.
Measures of Central Tendency
Mean … the most frequently used but is
sensitive to extreme scores
e.g. 1 2 3 4 5 6 7 8 9 10
Mean = 5.5 (median = 5.5)
e.g. 1 2 3 4 5 6 7 8 9 20
Mean = 6.5 (median = 5.5)
e.g. 1 2 3 4 5 6 7 8 9 100
Mean = 14.5 (median = 5.5)
Measures of Central Tendency
Median
… is not sensitive to extreme scores
… use it when you are unable to use the
mean because of extreme scores
Measures of Central Tendency
Mode
… does not involve any calculation or
ordering of data
… use it when you have categories (e.g.
occupation)
A Distribution Curve
English
Frequency
300
250
Mean: 54
200
Median: 56
150
Mode: 63
100
50
Mean = 53.78
Std. Dev. = 19.484
N = 4,253
0
0
20
40
60
English
80
100
The Normal Distribution Curve
In everyday life many variables such as
height, weight, shoe size and exam
marks all tend to be normally
distributed, that is, they all tend to look
like the following curve.
The Normal Distribution Curve
Mean, Median, Mode
0.025
0.02
0.015
0.01
0.005
0
0
20
40
60
80
100
It is bell-shaped and symmetrical about the mean
The mean, median and mode are equal
It is a function of the mean and the standard deviation
Measures that indicate the spread of
scores:
Range
Standard Deviation
Range
It compares the minimum score with the
maximum score
Max score – Min score = Range
It is a crude indication of the spread of the
scores because it does not tell us much
about the shape of the distribution and how
much the scores vary from the mean
Standard Deviation
It tells us what is happening between
the minimum and maximum scores
It tells us how much the scores in the
data set vary around the mean
It is useful when we need to compare
groups using the same scale
Calculating a Mean and a Standard Deviation
Sums
Means
Data
x
10
20
30
40
50
150
30
Deviation
x - Mean
-20
-10
0
10
20
0
0
Standard deviation =
Absolute
Deviation
|x - Mean|
20
10
0
10
20
60
12
Variance
Squared
Deviation
(x-Mean)²
400
100
0
100
400
1000
200
Variance
14.1421356
Interpreting Distributions
Mean
0.03
= 50
Std Dev = 15
0.025
0.02
0.015
34%
2%
0.01
0.005
34%
2%
14%
14%
0
0
10
20
30
40
50
60
70
80
90
100
scores
5
-3
0%
20
-2
2%
35
-1
16%
50
0
50%
65
+1
84%
80
+2
95
+3
sd
98% 100%
rank
Interpreting Distributions
School A
50
10
Mean
S.d.
School B
60
10
School C
70
10
0
0.045
0.04
0.035
0.03
0.025
0.02
0.015
0.01
0.005
0
0
20
40
60
80
100
120
Interpreting Distributions
School A
50
10
Mean
S.d.
School B
50
13
School C
50
16
0
0.045
0.04
0.035
0.03
0.025
0.02
0.015
0.01
0.005
0
0
20
40
60
80
100
120
Interpreting Distributions
National Mean
55
10
Mean
S.d.
School A
60
15
School B
40
15
0.045
0.04
0.035
0.03
0.025
0.02
0.015
0.01
0.005
0
-20
0
20
40
60
80
100
120
The Z-score
The z-score is a conversion of the raw
score into a standard score based on the
mean and the standard deviation.
z-score = Raw score – Mean
Standard Deviation
Example
z-score
Mean = 55
65 – 55
15
= 0.67
Standard Deviation = 15
Raw Score = 65
Converting z-scores into Percentiles
Use table provided to convert the z-score
into a percentile.
z-score
= 0.67
Percentile = 74.86% (from table provided)
Interpretation: 75% of the group scored
below this score.
Comparing School Performance
with National Performance
Mean
S.d.
National Mean
55
10
School A
60
15
School B
40
15
0.045
Z-score
for Mean of School A = (60 – 55)/10 = 0.2
0.04
0.035
0.03
0.025
0.02
0.015
0.01
0.005
0
A z-score of 0.2 is equivalent to a percentile of
57.93% on a national basis
Z-score for Mean of School B = (40 – 55)/10 = -1.5
A z-score of –1.5 is equivalent to a percentile of
-20
0
20
40
60
80
100
120
(100-93.32)%,
that is,
6.68%!
```
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