Home > Statistics > Grouped data > Raw Moments (Moments about origin), Central Moments (Moments about mean), Moment coefficient of skewness, Moment coefficient of kurtosis for grouped data example

Moments about mean Examples for grouped data ( Enter your problem )
  1. Moments about mean Examples
  2. Moments about origin Examples
  3. Moments about the value Examples

1. Moments about mean Examples





1. Calculate Moment about mean from the following grouped data
XFrequency
01
15
210
36
43


Solution:
Moments :
Mean `bar x=(sum f x)/n`

`=55/25`

`=2.2`

`x`
`(2)`
`f`
`(3)`
`f*x`
`(4)=(2)xx(3)`
`(x-bar x)`
`(5)`
`f*(x-bar x)`
`(6)=(3)xx(5)`
`f*(x-bar x)^2`
`(7)=(5)xx(6)`
`f*(x-bar x)^3`
`(8)=(5)xx(7)`
`f*(x-bar x)^4`
`(9)=(5)xx(8)`
010-2.2-2.24.84-10.64823.4256
155-1.2-67.2-8.6410.368
21020-0.2-20.4-0.080.016
36180.84.83.843.0722.4576
43121.85.49.7217.49631.4928
------------------------
--`n=25``sum f*x=55`--`=0``=26``=1.2``=67.76`


Now, calculate Central Moments

First Central Moment
`m_1=(sum f*(x-bar x))/n`

`=(0)/(25)`

`=0`



Second Central Moment
`m_2=(sum f*(x-bar x)^2)/n`

`=(26)/(25)`

`=1.04`



Third Central Moment
`m_3=(sum f*(x-bar x)^3)/n`

`=(1.2)/(25)`

`=0.048`



Fourth Central Moment
`m_4=(sum f*(x-bar x)^4)/n`

`=(67.76)/(25)`

`=2.7104`



Skewness `beta_1=(m_3)^2/(m_2)^3`

`=(0.048)^2/(1.04)^3`

`=(0.0023)/(1.1249)`

`=0.002`



Kurtosis `beta_2=(m_4)/(m_2)^2`

`=(2.7104)/(1.04)^2`

`=(2.7104)/(1.0816)`

`=2.5059`



Moment coefficient of skewness
`beta_1>0` : The distribution is positively skewed (a longer tail to the right).

Moment coefficient of kurtosis
`beta_2<3` : platykurtic (flatter with lighter tails)
2. Calculate Moment about mean from the following grouped data
XFrequency
103
1112
1218
1312
143


Solution:
Moments :
Mean `bar x=(sum f x)/n`

`=576/48`

`=12`

`x`
`(2)`
`f`
`(3)`
`f*x`
`(4)=(2)xx(3)`
`(x-bar x)`
`(5)`
`f*(x-bar x)`
`(6)=(3)xx(5)`
`f*(x-bar x)^2`
`(7)=(5)xx(6)`
`f*(x-bar x)^3`
`(8)=(5)xx(7)`
`f*(x-bar x)^4`
`(9)=(5)xx(8)`
10330-2-612-2448
1112132-1-1212-1212
121821600000
1312156112121212
1434226122448
------------------------
--`n=48``sum f*x=576`--`=0``=48``=0``=120`


Now, calculate Central Moments

First Central Moment
`m_1=(sum f*(x-bar x))/n`

`=(0)/(48)`

`=0`



Second Central Moment
`m_2=(sum f*(x-bar x)^2)/n`

`=(48)/(48)`

`=1`



Third Central Moment
`m_3=(sum f*(x-bar x)^3)/n`

`=(0)/(48)`

`=0`



Fourth Central Moment
`m_4=(sum f*(x-bar x)^4)/n`

`=(120)/(48)`

`=2.5`



Skewness `beta_1=(m_3)^2/(m_2)^3`

`=(0)^2/(1)^3`

`=(0)/(1)`

`=0`



Kurtosis `beta_2=(m_4)/(m_2)^2`

`=(2.5)/(1)^2`

`=(2.5)/(1)`

`=2.5`



Moment coefficient of skewness
`beta_1=0` : The distribution is perfectly symmetrical (like a normal distribution).

Moment coefficient of kurtosis
`beta_2<3` : platykurtic (flatter with lighter tails)
3. Calculate Moment about mean from the following grouped data
ClassFrequency
2 - 43
4 - 64
6 - 82
8 - 101


Solution:
Moments :
Mean `bar x=(sum f x)/(sum f)`

`=52/10`

`=5.2`

Class
`(1)`
Mid value (`x`)
`(2)`
`f`
`(3)`
`f*x`
`(4)=(2)xx(3)`
`(x-bar x)`
`(5)`
`f*(x-bar x)`
`(6)=(3)xx(5)`
`f*(x-bar x)^2`
`(7)=(5)xx(6)`
`f*(x-bar x)^3`
`(8)=(5)xx(7)`
`f*(x-bar x)^4`
`(9)=(5)xx(8)`
2 - 4339-2.2-6.614.52-31.94470.2768
4 - 65420-0.2-0.80.16-0.0320.0064
6 - 872141.83.66.4811.66420.9952
8 - 109193.83.814.4454.872208.5136
---------------------------
----`n=10``sum f*x=52`--`=0``=35.6``=34.56``=299.792`


Now, calculate Central Moments

First Central Moment
`m_1=(sum f*(x-bar x))/n`

`=(0)/(10)`

`=0`



Second Central Moment
`m_2=(sum f*(x-bar x)^2)/n`

`=(35.6)/(10)`

`=3.56`



Third Central Moment
`m_3=(sum f*(x-bar x)^3)/n`

`=(34.56)/(10)`

`=3.456`



Fourth Central Moment
`m_4=(sum f*(x-bar x)^4)/n`

`=(299.792)/(10)`

`=29.9792`



Skewness `beta_1=(m_3)^2/(m_2)^3`

`=(3.456)^2/(3.56)^3`

`=(11.9439)/(45.118)`

`=0.2647`



Kurtosis `beta_2=(m_4)/(m_2)^2`

`=(29.9792)/(3.56)^2`

`=(29.9792)/(12.6736)`

`=2.3655`



Moment coefficient of skewness
`beta_1>0` : The distribution is positively skewed (a longer tail to the right).

Moment coefficient of kurtosis
`beta_2<3` : platykurtic (flatter with lighter tails)
4. Calculate Moment about mean from the following grouped data
ClassFrequency
0 - 25
2 - 416
4 - 613
6 - 87
8 - 105
10 - 124


Solution:
Moments :
Mean `bar x=(sum f x)/(sum f)`

`=256/50`

`=5.12`

Class
`(1)`
Mid value (`x`)
`(2)`
`f`
`(3)`
`f*x`
`(4)=(2)xx(3)`
`(x-bar x)`
`(5)`
`f*(x-bar x)`
`(6)=(3)xx(5)`
`f*(x-bar x)^2`
`(7)=(5)xx(6)`
`f*(x-bar x)^3`
`(8)=(5)xx(7)`
`f*(x-bar x)^4`
`(9)=(5)xx(8)`
0 - 2155-4.12-20.684.872-349.67261440.6513
2 - 431648-2.12-33.9271.9104-152.45323.1941
4 - 651365-0.12-1.560.1872-0.02250.0027
6 - 877491.8813.1624.740846.512787.4439
8 - 1095453.8819.475.272292.05541133.1748
10 - 12114445.8823.52138.2976813.18994781.5565
---------------------------
----`n=50``sum f*x=256`--`=0``=395.28``=649.6128``=7766.0233`


Now, calculate Central Moments

First Central Moment
`m_1=(sum f*(x-bar x))/n`

`=(0)/(50)`

`=0`



Second Central Moment
`m_2=(sum f*(x-bar x)^2)/n`

`=(395.28)/(50)`

`=7.9056`



Third Central Moment
`m_3=(sum f*(x-bar x)^3)/n`

`=(649.6128)/(50)`

`=12.9923`



Fourth Central Moment
`m_4=(sum f*(x-bar x)^4)/n`

`=(7766.0233)/(50)`

`=155.3205`



Skewness `beta_1=(m_3)^2/(m_2)^3`

`=(12.9923)^2/(7.9056)^3`

`=(168.7987)/(494.0882)`

`=0.3416`



Kurtosis `beta_2=(m_4)/(m_2)^2`

`=(155.3205)/(7.9056)^2`

`=(155.3205)/(62.4985)`

`=2.4852`



Moment coefficient of skewness
`beta_1>0` : The distribution is positively skewed (a longer tail to the right).

Moment coefficient of kurtosis
`beta_2<3` : platykurtic (flatter with lighter tails)




This material is intended as a summary. Use your textbook for detail explanation.
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