Statistics may be classified as descriptive or inferential. While descriptive statistics are concerned with issues such as the average length of hospitalization of a group of patients, inferential statistics are used to address questions such as whether the differences in average lengths of patients in two groups are statistically, significantly different. Inferential statistics involve analysis of data as the basis for predictions related to the phenomenon of interest (Schmidt & Brown, 2011). Descriptive statistics deal with the collection and presentation of data used to explain characteristics of variables found in a sample. As its name implies, descriptive statistics describe, summarize, and synthesize collected data. Generally, calculations and information presented with descriptive statistics must be accurate.
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According to Polgar and Thomas (1993), the selection of appropriate descriptive statistics depends on the characteristics of the data being described. For example, in a variable such as incomes of patients, the best statistics to represent the typical income would be the mean the mean and / or the median. If there was a millionaire in the group of patients, the mean would give a distorted impression of the central tendency. In this case, the median would be appropriate. Mode is most commonly used when the data being described are categorical.
Similarly, the appropriate inferential statistics are determined by the characteristics of the data being analyzed. For example, where the mean is the appropriate descriptive statistic, inferential statistics will determine if differences between the means are statistically significant.
Polgar, S., & Thomas, S. A. (1993). Introduction to Research in the Health Sciences. Amsterdam: Elsevier.
Schmidt, N., & Brown, J. (2011). BOOK ALONE – Evidence-Based Practice for Nurses. Sudbury, MA: Jones & Bartlett Publishers.