Descriptive Statistics

Descriptive Statistics

Descriptive Statistics 

Description

Descriptive statistics involves the calculation of various statistical measures such as the measure of central tendency, the measure of variability, percentiles, and also the diagrammatic & graphical representation of data.

Why to use

To prove simple summaries about the sample data and its measures.

When to use

  • When you want to get different statistical values.
  • When you want to find out if there are any missing values in the data. 

When not to use

On textual data.

Prerequisites

It should be used on numerical data.


Input

Any dataset that contains numerical data.

Output

Statistical information of the selected features is displayed.

Statistical Methods used

  • Missing
  • Frequency (only for categorical data)
  • Frequency Percentage (only for categorical data)
  • Mean
  • Standard Deviation
  • Variance
  • Min
  • Q1
  • Median (Q2)
  • Q3
  • Max
  • Range
  • Mode
  • Skewness
  • Kurtosis
  • Standard error 

Limitations

-


Descriptive statistics are brief descriptive coefficients that summarize a given data set, which can be either a representation of the entire or a sample of a population. Descriptive statistics are broken down into measures of central tendency and measures of variability (spread).

Measures of Frequency: Count, Percent, and Frequency

Measures of Central Tendency: Mean, Median, and Mode

Measures of Dispersion or Variation: Range, Variance, Standard Deviation

Measure of lack of symmetry: Skewness

Measure of tailedness: Kurtosis

Measure of the statistical accuracy: Standard error

Partition Values: Percentile Ranks, Quartile Ranks.

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