Describe univariate, bivariate, and multivariate analysis.

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Univariate analysis is the simplest and easiest form of data analysis where the data being analyzed contains only one variable.

Example - Studying the heights of players in the NBA.

Univariate analysis can be described using Central Tendency, Dispersion, Quartiles, Bar charts, Histograms, Pie charts, and Frequency distribution tables.

The bivariate analysis involves the analysis of two variables to find causes, relationships, and correlations between the variables.

Example – Analyzing the sale of ice creams based on the temperature outside.

The bivariate analysis can be explained using Correlation coefficients, Linear regression, Logistic regression, Scatter plots, and Box plots.

The multivariate analysis involves the analysis of three or more variables to understand the relationship of each variable with the other variables.

Example – Analysing Revenue based on expenditure.

Multivariate analysis can be performed using Multiple regression, Factor analysis, Classification & regression trees, Cluster analysis, Principal component analysis, Dual-axis charts, etc.