Experiments in the sciences, business models and reports, use statistics. People involved in these fields generally have studied the meaning of statistical quantities, such as averages and standard deviation. Many colleges and universities require an introductory course in statistics as part of a professional program.
Each day people are inundated with statistical information from advertisements ("4 out of 5 dentists recommend"), news reports ("opinion poll show the incumbent leading by four points"), and even general conversation ("half the time I don't know what you're talking about"). Experts and advocates often use numerical claims to bolster their arguments, and statistical literacy is a necessary skill to help one decide what experts mean and which advocates to believe. This is important because statistics can be made to produce misrepresentations of data that may seem valid. The aim of statistical literacy proponents is to improve the public understanding of numbers and figures
Results of opinion polling are often cited by news organizations, but the quality of such polls varies considerably. Some understanding of the statistical technique of sampling is necessary in order to be able to correctly interpret polling results. Sample sizes may be too small to draw meaningful conclusions, and samples may be biased. The Alexa Internet web traffic reports, for example, are known to be biased for several reasons, one of which is that their toolbar only works with the Internet Explorer browser The wording of a poll question may introduce a bias, and thus can even be used intentionally to produce a biased result. Good polls use unbiased techniques, with much time and effort being spent in the design of the questions and polling strategy. Statistical literacy is necessary to understand what makes a poll trustworthy and to properly weigh the value of poll results and conclusions.
A problem also occurs with literacy because of the work of statisticians. The legibility of numerical tables is an example given early in the recent book by Richard M. Heiberger & Burt Holland, Statistical Analysis and Data Display (New York, N.Y.: Springer, 2004). In their example, rather than an incorrect, confusing, collection of numbers in misaligned columns, the statistician must present results legibly by lining up the decimal points so the visual presentation is more organised [Heiberger].