Statistical Concepts – MBA Accouting
Statistical concepts vary in use and application. The practical use of statistics can be summed up in a simple ideal – the world of business is more complex and therefore more information is needed to adequately define the reasons, issues, and concerns underlying such complexity. Central tendency, standard deviation, and the group; mean, mode, and median, are examples of the statistical concepts that aid managers in identify and remedying problems that arise in their companies. Finding ways to address problems and concerns correctly creates the obligation of becoming familiar with these statistical concepts.
Central tendency is described as locating the centralized value that summarizes a set of data. There are different measures of central tendency, but central tendency is similar to what is called the average of data. Different types of central tendency are: arithmetic mean, weighted mean, median, mode, and geometric mean. These statistical concepts, accurately applied, will seek to find the average of a certain collection of data, whether it is a population or a sample of a population, central tendency will find the middle ground of a set of information. Many areas of business exemplify the practical application of central tendency. Some more overt than others. Such as:
� Sports professionals in the NFL, NBA, and Major League are measured by the central tendency of their scoring. Basketball players have an average of the points they score. Football players have an average of the amount of yards they run in a season. Major League baseball players have an average of the hits per season. The statistics are important when players are drafted and traded to other teams and in the creation of sports contracts, where the players may have to renegotiate their contracts and ask for better salaries.
� Truck drivers have an obligation to keep track of certain maintenance functions of their trucks. Specifically, gas prices are very important because many ties truck drivers must pay for their own gas while transporting items. Knowing the average price of gas will allow truck drivers more leverage in deciding when and where to stop for gas. This seems futile to some, but for a person who make a living driving trucks this can be the difference between a slim pay check and healthy paycheck at the end of the pay period.
� Car rental agencies also must monitor the average price of upkeep on the cars they rent. This is vital because the cost of the maintenance of rental cars, will determine if the price of rental transferred to the customers will need to be modified.
Standard deviation is based on the variance from the acquired mean. Variance is the mean of the squared deviations from the mean of a set of data. These are measures of dispersion. Unlike central tendency, dispersion analyzes the spread of a set of data and not only the average or mean. Standard deviation gives a bigger picture of the actual data set. Undoubtedly, the mean is helpful; standard deviation is regarded highly when a sample is needed as in the instance:
� Hospitals may need to compare some of the characteristics of its patients. There is often the need to determine where most monies donated to a hospital may need to be allocated. For instance there is a need to know how many patients die from natural-age related reason compared to those patients that pass away from chronic disease. Standard deviation may help identify how many patients in a specific sample use hospital facilities for one reason and how many other patients use the facilities for alternative reasons.
âÂ?¢ The time limits of pizza delivery men for certain branches of a pizzeria chain may determine which branches should be re-staffed and which branches are consistently meeting the “30 minutes or less” criteria.
Mean, median, and mode are specific types of central tendency that aid managers and businessperson in making vital decisions to their individual welfare or company’s success. There are three types of mean: population, weighted, and geometric means. Mean is determined by adding all of the data values and dividing the total by the number of values added together. Mean is an average of data in a set such as:
� The mean amount of sales commissions produced by sales persons will allow managers to determine who is entitled to a raise or whose employment needs to be reconsidered.
� The Patent & Trademark Office of the federal government can keep track of how many patents it issues to the automobile manufacturing companies in the US.
Extremely large or small numbers can throw off the value but even in that instance the median can allow a clearer interpretation of the information. Median is the number in the middle of a data set. Ordering the numbers ascending
and choosing the middle number is identifying the median. Or in the instance of an even number of values in a set, averaging the two middle numbers will produce the median. This is important when there is large or small number that could misconstrue the mean.
� Home values in a certain area would be better relayed in terms of median value rather than mean value. Averaging homes for 10K, 15K, 25K, 30 K and 1.5M will result in a mean value that would easily intimidate most homebuyers. However, the median of 25K would more likely be close to the amount a potential homebuyer would pay. This of course would be helpful to real estate sales agents and brokers.
Mode is helpful also when performing research that involves surveys of samples. This definitely helps managers identify what item or product was most successful among the survey participants. The mode reflects the value that appears most in a sample. It frequently describes ordinal and nominal values. Such as:
� A survey, such as which of 5 bath oils consumers like most will definitely need a modal interpretation of data.
� Customer service surveys that ask questions about the service provided by employees are a good example. If 5s continue to be submitted as the answer with 5 being the best, can be easily interpreted to mean that the service is top-notch.
Central tendency, standard deviation, and the group; mean, mode, and median all seek to make it easier for managers and company researchers to determine in what areas they need to improve or perform further inquiry. As useful as they all seem, each concept needs to be independently studied further before one is chosen over the other in order to determine the best concept is used to yield the proper desired results.