Scales of measurement and presentation of statistical data

Abstract

Measurement scale is an important part of data collection, analysis, and presentation. In the data collection and data analysis, statistical tools differ from one data type to another. There are four types of variables, namely nominal, ordinal, discrete, and continuous, and their nature and application are different. Graphs are a common method to visually present and illustrate relationships in the data. There are several statistical diagrams available to present data sets. However, their use depends on our objectives and data types. We should use the appropriate diagram for the data set, which is very useful for easily and quickly communicating summaries and findings to the audience. In the present study, statistical data type and its presentation, which are used in the field of biomedical research, have been discussed.

Keywords: Graphical presentation; qualitative variable; quantitative variable; scales of measurement.

Figure 1

(a) Simple bar graph showing mean age between sex, (b and c) multiple bar graph and line graph showing mean age and BMI between sex, (d) sex distribution of the data, (e) histogram showing nature of the BMI distribution, (f) error bar graph showing mean BMI as per sex, (g) box plot showing age distribution as per sex, (h) scatter diagram showing linear relationship between age and BMI, (i) Bland–Altman plot showing relationship between SBP difference and their average values, (j) Forest plot showing relative risk and associated confidence intervals observed from five different studies for the exposure group as compared to nonexposure group. BMI: Body mass index, SBP: Systolic blood pressure