# Everyday Life Statistics

1685 Words 7 Pages
In our everyday life statistics are used in some form probably more than we realize. At home, you could be keeping a running average of your utility bills to see if differences appear. If you are looking at paying off your mortgage five years early, you will need to calculate the amount needed to accomplish this achievement. Some of us that may have purchased stocks will keep stats on the highs and lows of their investments to help determine a time to possibly sale the stock. The use of statistics in our personal lives may be overlooked as being a statistic; it is just what we have to do on a normal day. However, in the business world we keep statistics to look for changes in a shops production to maintain control and to stop defaults …show more content…
By measuring, the amount of customers that are in the facility at different times of the day a manager can determine how many employees they will need at different periods during the shifts. Lunch and dinner time is most likely the time frame when you will need the most employees and between 1:00 pm and 4:00 pm could be the slowest times. This statistic is reliable to keep the cost down for the business and improve the profit …show more content…
The Six-Sigma program is good example of statistics. It consist of a multitude of different formulas to find the answer to the problem or of the success. In the training I participated in fifteen years ago, most of the people were not actually taking samples of the process they were working on. In some cases they would ask one person out of a group, how many widgets per day are scrapped in that shop? The answer was just a guess, the actual number of scrap parts was not tracked. In reality, the best practice would be to look at the scrap rate in that shop on the software that record and track that data. The word of one employee cannot be reliable. The data that was used in all of the presentations of 16 people, 100% of the time showed a positive change in the process. Because I actually knew what happened in those shops I would guess that 60% of the calculations were correct and the remaining ones were made up to show an improvement. This happens to help make the person doing the project look good or even to prevent the person from having to start a new project if the probability of the parts being scrapped was 2% then the improvement could be a bust. In this program, we were calling the cost savings from the data collected “monopoly money.” For the statistics to be reliable honesty