P1 Unit 3 Data Analysis

There are many different ways to describe the data we collect and all are important when conducting business. The mean of a data set is the sum divided by the # of observations. Now saying exactly what a mean is can be helpful, applying it to the business world makes understanding it a lot easier. Mean can be used in a business environment by both tax offices and retailers when collecting income from a group of people; in this case both groups are interested in the total amount of money that happens to be available. Companies can determine the mean salary for their business to know the average amount they are paying employees (some employees may make more or less than the mean).

The textbook says that Variance is "based on the difference between
Investors often use z-scores to calculate whether or not a company is in good financial health. By collecting data, such as, working capital and retained earnings investors can see if a company falls into the red zone which is under 2.0 then a company is headed toward bankruptcy. Where as if a company is above 2.0 then they are not nearing bankruptcy.

N is the number on elements in a population and n is the number of elements in a sample. It is extremely important to understand and know the difference when putting together/ solving equations because if you mess up either one of the numbers than you're answers will be off as well.

In business, errors can be costly, especially in positions of power. It is crucial that anyone who is using any type of descriptive statistic understands the risk that could happen if even one number is off when dealing with a problem. The mean, variance, standard deviation, z-score, N, and n are all vital elements to the role descriptive statistics plays in the business world. From retail managers to supply chain managers, anyone can benefit from understanding and applying all six of these terms to everyday business life in order to produce a thriving economy and