Statistical Equations

The use of statistical equations are fundamental to the science of statistics. One can not practice statistics, or quantify and analyze numerical data without the use of at least one statistical equation. Upon first glancing at many of the statistical equations they may seem impossible, as if you were trying to read a foreign language without ever having been introduced to such a language. Stay calm. With some practice and discipline you will be able to decipher the language of statistics in no time. Statistical equations vary in difficulty from easy to ‘what the heck does that mean?!’ The most used statistical equations include, but are not limited to, sample and population mean, standard error, standard deviation, sample variance, binomial equations, mean of a binomial distribution, and combinations and permutations. Some of the more difficult statistical equations include Fisher Skewness and Unbiased Estimator of Population Sample Variance. Computer programs such a Microsoft Excel can be extremely helpful when working with statistical equations, and from personal experience I would recommend becoming familiar with such a program.

One very important statistical equation is standard deviation. Standard deviation is used in order to measure the variance that occurs within a set of data. Finding the standard deviation of a set of data is important in solving many statistical problems. Another piece of information that is essential to solving many statistical problems is the sample mean. A sample is a subset of a larger population. The statistical equation for sample mean will provide an average of all of the items in the sample. The statistical equation for combinations provides the possible number of outcomes that can occur without repetition. This becomes very important when studying probability. An example of when the formula for combination would come in hand is during a card game. If you have five cards in you hand out of a 52 card deck, calculating the combination would calculate how many different hands were possible with out repetition. Fisher Skewness is a statistical equation that can measure the amount of asymmetry that is present in a binomial distribution. If the smaller end of the function, or the left tail, is more pronounced than the larger end, or the right tail, then the function has a negative skewness. If the opposite is true than the function is said to have a positive skewness.

Statistics and statistical equations are important in many areas of life and a variety of different careers. Statistics can be used to measure business performance, giving the company the knowledge that they need to improve their business performance. The use of statistics is important to all areas of economics and commerce. Anthropologists and government officials use statistical equations to collect stats on social, cultural, and economic issue. This information can then be used to determine what policies are effective and what policies are not effective. Advertising companies used statistics to determine how to form their marketing campaigns. Statistics and equations provide us with a means of quantifying information and data that we wouldn’t otherwise be able to express.