skewness

Skewness and kurtosis

The skewness in basic term implies off centre so does in statistics, it mean lack of symmetry. With the help of skewness one can identity the shape of the distribution of data. Kurtosis on the other hand refers to the pointedness of a peak in the distribution curve. The main difference between skewness and kurtosis is that the former talk of the degree of symmetry, whereas the later takeoff the degree of symmetry whereas the latter tall of the degree of peakedness in the frequency distribution..

 Data can be distribution in many way like spread out more on left on the right or evenly spread.  When the data is scattered uniformly at the central point it called as normal distribution. It is perfectly symmetry, bell shaped curve.Here all the three mean, mediyan, mode line at one point.

Skewness and kurtosis are two important

Character of distribution that are studied in descriptive statistics. To further comprehed the understanding.  The term skewness is used to mean the absence of symmetry from the mean of data set.it is characterized of the deviation from the mean to be greater on one side than the other.

The characteristic of a frequency distribution that ascertain it s symmetry about the mean is called skew ness. On the otherhand kurtosis mean the relative pointedens of the standared bell curve defined by the frequency distribution.. Skewness is measure of the degree of lopsidedness in the frequency distribution. Convery kurtosis is a measure of degree of tiredness in the frequency distribution.  Skewness is an indicator of lack of symmetry. Both left and right side of the curve are unequal with respect to the central point

Skewness show how much and in which directed the values deviate from the mean. For

A normal distribution the value of skenwss and kurtosis statistics is zeros. The cruve of the distribution is thatis skewss.

Definition

 In kurtosis is defined as the parameters of relatively  sharpened of thepeak of relatively sharpened of the peaked probability curve.

                                                                                    

In kurtosis is defined as the parameters of relatively  sharpened of thepeak of relatively sharpened of the peaked probability curve.

                                                         

Table 1 sarveshwar India’s blog

Moment number	name	Measure of
1	mean	Central tendency
2	variance	dispersion
3	skewness	Symmetry
4	kurtosis	shape

  

Skewness and kurtosis The skewness in basic term implies off centre so does in statistics, it mean lack of symmetry. With the help of skewness one can identity the shape of the distribution of data. Kurtosis on the other hand refers to the pointedness of a peak in the distribution curve. The main difference between skewness and kurtosis is that the former talk of the degree of symmetry, whereas the later takeoff the degree of symmetry whereas the latter tall of the degree of peakedness in the frequency distribution.. Data can be distribution in many way like spread out more on left on the right or evenly spread. When the data is scattered uniformly at the central point it called as normal distribution. It is perfectly symmetry, bell shaped curve.Here all the three mean, mediyan, mode line at one point. Skewness and kurtosis are two important Character of distribution that are studied in descriptive statistics. To further comprehed the understanding. The term skewness is used to mean the absence of symmetry from the mean of data set.it is characterized of the deviation from the mean to be greater on one side than the other. The characteristic of a frequency distribution that ascertain it s symmetry about the mean is called skew ness. On the otherhand kurtosis mean the relative pointedens of the standared bell curve defined by the frequency distribution.. Skewness is measure of the degree of lopsidedness in the frequency distribution. Convery kurtosis is a measure of degree of tiredness in the frequency distribution. Skewness is an indicator of lack of symmetry. Both left and right side of the curve are unequal with respect to the central point Skewness show how much and in which directed the values deviate from the mean. For A normal distribution the value of skenwss and kurtosis statistics is zeros. The cruve of the distribution is thatis skewss. Definition In kurtosis is defined as the parameters of relatively sharpened of thepeak of relatively sharpened of the peaked probability curve. In kurtosis is defined as the parameters of relatively sharpened of thepeak of relatively sharpened of the peaked probability curve.   Table 1 sarveshwar India’s blog Moment number name Measure of 1 mean Central tendency 2 variance dispersion 3 skewness Symmetry 4 kurtosis shape picture 2

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