In statistics, univariate analysis involves examining various measures to understand the distribution and characteristics of a single variable. Position measurements such as quartiles, percentiles, and deciles help to divide the data set into equal parts and give insight into its spread.
Kurtosis (or skewness) is a shape measure that measures how steep or flattened a curve or distribution is.
This coefficient indicates the amount of data that is close to the mean, so that the higher the degree of kurtosis, the steeper (or pointed) the shape of the curve will be.
Asymmetry is the measure that indicates the symmetry of the distribution of a variable with respect to the arithmetic mean, without the need for graphical representation. Skewness coefficients indicate whether there are the same number of elements to the left and right of the mean.
Negative skewness: the tail of the distribution becomes longer for values below the mean.
Symmetric: there are the same number of elements to the left and right of the mean. In this case, the mean, median and mode coincide. The distribution fits the shape of the Gaussian bell, or normal distribution.
Positive skewness: the tail of the distribution becomes longer (to the right) for values above the mean.
DISPERSION MEASURES
COEFFICIENT OF VARIATION
MOMENTS
VARIANCE
RANGE
POSITION MEASUREMENTS
CUANTILES
Percentiles K = 100
Deciles K = 10
Cuartiles K=4
MEASURES OF CENTRAL TENDENCY
FAD
is the value with the highest frequency in one of the data distributions
MEDIAN
is the middle number of a group of numbers ordered by size. If the number of terms is even, the median is the average of the two central numbers
HALF
It is found by adding the total values in the variance and dividing by the number of observations
values located in the center of a set of data ordered according to their magnitude.