Descriptive statistics are customarily used to explain the primary features of data used in a study as they give summaries about the samples and measures. Descriptive statistics have been met with various lines of the course, and it has been associated with various experiences. In this study, the discussion will be exploring the use of descriptive statistics.
While using descriptive statistics, one can understand the features of a set of data and come up with summaries regarding the samples and measures of the data. Mean, median and mode are the recognized types of descriptive data used across various levels of statistics. In these concepts of statistics, one can understand and appreciate the use of graphs, tables and general discussions to enhance the understanding of the data being analyzed ( Baesens, 2015 ).
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Descriptive statistics can collect and organize data, and also compare a significant amount of data in more manageable forms. The process of collecting the data is a natural process that only describes and summarizes the data. They do not correlate data or create statistical modeling relationship among the various variables that might result in inferred conclusions. Descriptive statistics are however limited in many ways as it only allows a researcher to make summations about the people and objects that have been measured. The data collected cannot be used to generalize other people or objects.
Descriptive statistics can be used in the future in weather forecasting where the previous weather conditions can be compared to the current requirements to be able to predict the future weather. It can as well be used in preparations for emergencies as statistics can show when danger or natural disaster can occur.
Reference
Baesens, B. (2015). Fraud analytics using descriptive, predictive, and social network techniques: A guide to data science for fraud detection . Hoboken, New Jersey: Wiley
