# The Difference between Univariate and Multivariate Financial Analysis

In the business world, it is important to study the set of data to keep the business in check. It helps business leaders to make important decisions by studying the factors that affect the business. Financial analysis is the manner of understanding the financial condition of the business through mathematical and statistical methods. This gives way for management to assess the stability and liquidity of the business.

Statistics is an important tool for businesses since it deals with collection of data and interpreting them through mathematical methods and models. Statistics can also use the existing data to project future outcomes. In business, financial assessment can be done through univariate and multivariate analysis.

Analysis of specific factors affecting the business can be done through univariate analysis. Univariate analysis is the simplistic way of analyzing data. It deals with the data one variable at a time. It takes on the basics of statistics like mean, median and mode. Given a set of data, analysis of the variable is done by how close the value to the mean, median or mode. It analyzes central tendencies. Measuring central tendencies is describing a variable in respect to the entire set of data. Given a distribution, the data set tends to gather around a certain value. It can also be that the entire set of data can be described by one value.

Because several factors can affect a business, using univariate analysis may not be enough. The limitation of the univariate analysis is in its simplicity. It is purely descriptive and the predicting future occurrence does not take into consideration the changes in external factors or variables. When dealing with different variables, multivariate analysis comes into play.

Multivariate analysis can describe and infer on a set of data even when several variables are involved. In the advent that this variable changes, multivariate analysis can still see the effect of such variable change to other variables and to the data as a whole. An example of multivariate analysis is though linear regression. Linear regression estimates a set of data using drawing a linear function based on the distribution of the data.  Linear regression is often used pricing models and predicting risks in investments.

Business decisions are not made by instincts and gut-feel but by analysis of data. Risks and uncertainties are expected. Minimizing those risks can be achieved by financial analysis. Thorough inspection using statistical methods is expected from business leaders before decisions are made.

References:

Franke, J., Hardle, W.,& Hafner, C. (2008). Statistics for Financial Markets. Berlin: Springer

http://www.ph.ucla.edu/class/chs/chs219/UNIVAR.pdf
http://www.uwsp.edu/psych/cw/statmanual/