Use this frequency distribution table to calculate the following: 1.Coefficient of variation 2.Geometric mean 3.Measure of skewness
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
Use this frequency distribution table to calculate the following:
1.Coefficient of variation
2.Geometric mean
3.Measure of skewness
|
Interval (cm) |
frequency |
Cum more than frequency |
Cum less than frequency |
Class midpoint |
F.M |
Frequency percentage % |
|
40≤49 |
3 |
3 |
30 |
44.5 |
133.5 |
10 |
|
50≤59 |
9 |
12 |
27 |
54.5 |
490.5 |
30 |
|
60≤69 |
10 |
22 |
18 |
64.5 |
645 |
33.3 |
|
70≤79 |
5 |
27 |
8 |
74.5 |
372.5 |
16.67 |
|
80≤89 |
2 |
29 |
3 |
84.5 |
169 |
6.67 |
|
90≤99 |
1 |
30 |
1 |
94.5 |
94.5 |
3.33 |
|
TOTALS |
30 |
|
|
|
1905 |
100 |
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