Importance of Statistics in Business Decision Making

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What is Statistics?

Statistics is the collection, compilation, presentation, representation, analysis and interpretation of numeric and non-numeric data for effective decision-making.

Application of Statistics in Business Decision-making

In business, numbers are very essential even low numbers make significant difference. Statistics provide facts for effective business decision making. Without statistics, business managers will be taking decisions based on assumption, and decision taken on assumptions, cannot produce effective results. 

Statistical analysis helps in the measurement of quantitative relationships between business or economic variables. It is not sufficient to say that one variable is a function or is dependent of the other. For example, it is not enough to say sales is a function of advertisement.  There is need to measure if advertisement really affects sales, and to what extent is sales dependent of advertisement. Statistical tool such as regression helps us to be precise.

In this time of big data, statistical tools are used to summerise or condense a mass of data . They help to achieve a clearer understanding of big data. Statistical methods are devices which help to make big data more meaningful. The reality behind the numbers becomes readily understandable.

Business is characterised by uncertainties and risks, statistics therefore, aids in business decision-making as it is method of decision-making, under conditions of uncertainties involving calculable risks when numerical data are available. The use of statistical methods is becoming increasingly relevant in business decision-making, and in deed in every other facet of human endeavor. Proper data analysis enables business owners and managers to make rational decisions based on facts rather than depend on trial and error.

Important Statistical Tools for Business Decision-making

1. Measures of central tendencies/measures of average — Mean, mode and median

2. Regression

3. Correlation

4. Time series and forecasting

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