Descriptive statistics, Part II: Most commonly used descriptive statistics

Mary L McHugh1

  • 1School of Nursing, University of Colorado Health Science Center, Denver, CO, USA. mary.mchugh@uchsc.edu

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Descriptive statistics describe or summarize relevant characteristics of a sample and aid in the analysis of data of interest. When analyzing large quantities of data and developing an inference, one needs to identify a value representative of the entire data set. Characteristics such as central tendency, extreme values, range of measurements, or the most repeated value can help better understand the data.
The central tendency is the most conventionally used data characteristic. It is a...
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Measures of central tendency are tools used in biostatistics to identify the average or center of a dataset. They offer a single representative value for understanding and summarizing data distribution.
The mean is one such measure, calculated by totaling all values in a dataset and dividing by the number of values. For instance, the mean blood pressure reading (120, 130, 140, 150) would be 135. However, the mean can be affected by extreme values or outliers.
The median, another measure,...
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When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
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In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
Percentiles are a type of fractile that partition data into...
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