Descriptive and Inferential Statistics
Whether doing original research or conducting literature reviews, one must conclude what a powerful and versatile tool statistics are in the hands of researchers. From basic statistics such as data description, to using complex statistical methods to foresee future patterns or strengthen scientific claims about current climates, the role of statistics in research cannot be taken lightly and is essential in almost any field, especially in psychology. The statistical method is divided into two main branches called descriptive and inferential statistics. Descriptive statistics is a summary of information and the data presented is easily understood. Inferential statistics are much more detailed and are used to draw conclusions about hypotheses or determine probabilities of an outcome. Both allow researchers to describe, graph and present data for a general audience or more technical for the professionals. Without statistics, researchers lose that vital tool that allows them to move from hypothesis to conclusion.
The ability to describe data is an essential asset that comes with statistics. Once strong, reliable, and valid data is collected by the researcher, he or she must then make sense of the data and more importantly, make it understandable. Certain clues to a certain conclusion may be ascertained from simply looking at raw data, descriptive statistics provides an easier way to conclusion. Describing the central inclination of data is done with basic descriptive statistics such as mean, median and mode; data deviation from the center is shown by standard deviation, range and variance. These descriptive methods provide the researcher graphical understanding of the data frequency. Helpful graphics, such as the five-number summary displayed by a box plot, alerts the researcher to outliers in the data and the affect these outliers have on the statistics (Weiss & Weiss,...