Qnt 351 - Statistics in Business

Statistics in Business

QNT 351

Statistics in Business

        Statistics is numerical information that has been collected, organized, analyzed, and can be presented in a form that is required based on the information that has been requested. Statistics is important in the decision making process. Managers gather all the data needed, analyze that data, and make decision based on the outcome of the research data.

        There are two types of statistics: descriptive and inferential.  Descriptive statistics refers to methods of data collection and how it is organized into a format that is informative for those who requested the data. A financial report is an example of descriptive statistics.

        Inferential statistics refers to a sample of a specific population, meaning a certain group, which could be students, teachers, or government officials, or it could be specific objects like cars or shoes. In inferential statistics you are taking a group of people or objects of interest and measuring them. This is not the entire population, this is only a sample, therefore, you can only assume something based on the data collected.

        There are variables that are associated with data collection as well. Those variables are qualitative and quantitative. Qualitative variables can't be changed. This includes things like age, sex, and ethnicity. While Quantitative analysis can be changed, an example would be height, not everyone is the same height or weight. Not every company makes the same amount of profit, so when using it in financial analyses, each amount is different. These are quantified depending on the level of measurement.        

        There are four types of measurements as listed in the chart in chapter 1 of our textbook; nominal, ordinal, interval and ratio. Depending on what you are measuring will determine which type of measurement that you will use. These are used in business on a daily basis.

        Statistics plays a major role in the business decision-making process. Managers collect, analyze, and interpret data on a daily basis. When I worked in a call center, the time we were on calls were measured. Our managers gathered that data and if our call times were to high, we would be talked to and they would try to find out why our call times were so high. Another example would be collecting data about employee productivity. The manager could measure things like how many tasks the employee completes in a certain amount of time. Another example would be using data to analyze how many units are produced in a given period of time. You could use that data to improve your processes to increase your unit production, this information will also lead you to exactly where in the production process there is a problem and from there a manger can determine how to go about fixing the problem in order to increase production.