Business and finance managers make better decisions when they have adequate information available to make those decisions. Quantitative methods provide additional information to assist managers in making business and finance decisions that will impact the organizations. Common quantitative methods include regression analysis, the use of probabilities and analyzing statistical data.
Regression analysis allows the management to use their own observations regarding related information to make predictions about the future. Management would first identify the related sets of data they would like to observe and collect the data. The data would be plotted on a graph, giving management a visual depiction of the relationship between the sets of data. That data would most likely not fall in a straight line on the graph, but a reasonable assumption about the relationship could be made. Managers might use regression analysis to analyze the relationship between interest rates and loan periods.
Normal probability is commonly depicted as a bell curve. In the bell curve, the majority of observations fall in the mid-range of the curve. An even number of observations fall at the high end and at the low end of the bell curve. Management might use normal probability to predict the level of quality defects that they will experience on a production line. If each product needs to meet required specifications within a range, management could expect that the majority of products would fall in the mid-range, while an even number of units would fall at the high end and at the low end of the specification range.
Statistics is a method of predicting what percentage of transactions will have a particular result. This is done by collecting and analyzing random samples from a larger group of transactions. Random sampling is used for statistical analysis because it is too expensive or unfeasible to analyze every transaction. Management might sample a percentage of finished products and check for defects. The percentage of defects that are found is applied to the entire production run to estimate how many products might have defects.