The Lens Model is extremely helpful tool that extensively used by today's investors. Since investors should always predict value and growth of the market, which is the same as analyzing decision situations that involve uncertainty, the Lens Model is an exact right tool for this job. .
Statistical technique also can help to establish the relationship of an outcome, such as the sales of a company, and one or more cues, such as family formations, gross domestic product, per capita income, and other economic indicators. By measuring exactly how large and significant each cue has historically been in its relation to the outcome, the future value of the outcome can be predicted. Essentially, Lens model attempts to measure the degree of correlation between the cues and outcome, thereby establishing the latter's predictive value. For example, a manufacturer of baby food might want to determine the relationship between sales and housing starts as part of a sales forecast. Using a technique called a scatter graph, it might plot on the X and Y axes the historical sales for ten years and the historical annual housing starts for the same period. A line connecting the average dots would reveal the degree of correlation between the two factors by showing the amount of unexplained variation-represented by the dots falling outside the line. It would demonstrate a direct relationship between baby food sales and housing starts, meaning that one could be predicted on the basis of the other. The proportion of dots scattered outside the regression line would indicate, on the other hand, the degree to which the relationship was less direct, a high enough degree of unexplained variation meaning there was no meaningful relationship and that housing starts have no predictive value in terms of baby food sales. A correlation coefficient of 1 means the relationship is direct-baby food and housing starts move together; 1 means there is a negative relationship-the more housing starts there are, the less baby food is sold; a coefficient of zero means there is no relationship between the two factors.