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THE MEAN DEVIATION:-
? The mean deviation of a set of data is defined as 
the arithmetic mean of the deviations measured 
either from the mean or from the median, all 
deviations are being counted as positive.
M.D=                         For sample data
M.D=                         For Population Data
Page 2


THE MEAN DEVIATION:-
? The mean deviation of a set of data is defined as 
the arithmetic mean of the deviations measured 
either from the mean or from the median, all 
deviations are being counted as positive.
M.D=                         For sample data
M.D=                         For Population Data
? Mean Deviation is an absolute measure of 
dispersion. It’s relative measure is known as the co-
efficient of mean deviation, is obtained by dividing 
the mean deviation by the average used in the 
calculation of deviation.
Co-efficient of M.D=               or                 
Example#01: Calculate the  M.D and it’s Co-efficient 
from given data
29,35,38,40,55,60,65,70
Page 3


THE MEAN DEVIATION:-
? The mean deviation of a set of data is defined as 
the arithmetic mean of the deviations measured 
either from the mean or from the median, all 
deviations are being counted as positive.
M.D=                         For sample data
M.D=                         For Population Data
? Mean Deviation is an absolute measure of 
dispersion. It’s relative measure is known as the co-
efficient of mean deviation, is obtained by dividing 
the mean deviation by the average used in the 
calculation of deviation.
Co-efficient of M.D=               or                 
Example#01: Calculate the  M.D and it’s Co-efficient 
from given data
29,35,38,40,55,60,65,70
29              -20                            20
35           -14                      14
38           -11                       11       
40           -9                          9
55            6                          6
60           11                        11
65           16                       16
70           21                        21
?xi=392 ?
=108
Page 4


THE MEAN DEVIATION:-
? The mean deviation of a set of data is defined as 
the arithmetic mean of the deviations measured 
either from the mean or from the median, all 
deviations are being counted as positive.
M.D=                         For sample data
M.D=                         For Population Data
? Mean Deviation is an absolute measure of 
dispersion. It’s relative measure is known as the co-
efficient of mean deviation, is obtained by dividing 
the mean deviation by the average used in the 
calculation of deviation.
Co-efficient of M.D=               or                 
Example#01: Calculate the  M.D and it’s Co-efficient 
from given data
29,35,38,40,55,60,65,70
29              -20                            20
35           -14                      14
38           -11                       11       
40           -9                          9
55            6                          6
60           11                        11
65           16                       16
70           21                        21
?xi=392 ?
=108
putting the values
M.D=
M.D= 13.5 
Now co-efficient of Mean Deviation
Coefficient of M.D=
=
Co-efficient of M.D= 0.27
Page 5


THE MEAN DEVIATION:-
? The mean deviation of a set of data is defined as 
the arithmetic mean of the deviations measured 
either from the mean or from the median, all 
deviations are being counted as positive.
M.D=                         For sample data
M.D=                         For Population Data
? Mean Deviation is an absolute measure of 
dispersion. It’s relative measure is known as the co-
efficient of mean deviation, is obtained by dividing 
the mean deviation by the average used in the 
calculation of deviation.
Co-efficient of M.D=               or                 
Example#01: Calculate the  M.D and it’s Co-efficient 
from given data
29,35,38,40,55,60,65,70
29              -20                            20
35           -14                      14
38           -11                       11       
40           -9                          9
55            6                          6
60           11                        11
65           16                       16
70           21                        21
?xi=392 ?
=108
putting the values
M.D=
M.D= 13.5 
Now co-efficient of Mean Deviation
Coefficient of M.D=
=
Co-efficient of M.D= 0.27
The Variance and Standard Deviation:-
The variance is the set of observations is 
defined as the mean of the deviations of all the 
observation from their mean .When it is calculated from
the entire population, the variance is called population 
variance. If instead, the data from sample  are used to 
calculate the variance, it is referred to as the sample 
variance. The symbolic definition for variance is 
=                   , For population data
, For sample data
=
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FAQs on PPT: Standard Deviation & Coefficient of Variance - Engineering Mathematics - Civil Engineering (CE)

1. What is the formula to calculate standard deviation?
Ans. The formula to calculate standard deviation is the square root of the variance. It can be calculated by finding the difference between each data point and the mean, squaring the result, summing up all the squared differences, dividing by the total number of data points, and then taking the square root of the result.
2. How is standard deviation different from variance?
Ans. Standard deviation and variance are both measures of dispersion, but they differ in terms of the unit of measurement. Standard deviation is the square root of the variance and is expressed in the same unit as the original data, while variance is the average of the squared differences from the mean and is expressed in squared units.
3. What does a high standard deviation indicate?
Ans. A high standard deviation indicates that the data points in a dataset are widely spread out from the mean. It suggests that there is a large amount of variability or dispersion in the data. In other words, the values in the dataset are far from the average, indicating a less consistent or predictable set of values.
4. What does a low coefficient of variation mean?
Ans. A low coefficient of variation indicates that the variability in a dataset is relatively small compared to the mean. It suggests that the data points are close to the average, indicating a more consistent or predictable set of values. A low coefficient of variation is often considered desirable in certain applications, such as quality control, where consistency is important.
5. How can the coefficient of variation be useful in comparing datasets?
Ans. The coefficient of variation (CV) can be useful in comparing datasets because it allows for a relative comparison of variability between datasets with different means and units of measurement. By dividing the standard deviation by the mean and multiplying by 100, the CV provides a percentage value that represents the relative variability. This enables researchers or analysts to assess and compare the relative consistency or variability of different datasets, even if they have different scales or units.
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