A statistical tool designed to automate the process of performing a non-parametric test used to determine if there is a significant difference between two related samples, or to assess whether the median of a population is equal to a specified value. It takes paired data or a single sample dataset as input, calculates the differences between paired values (or values and the hypothesized median), ranks the absolute values of these differences, and then sums the ranks of the positive and negative differences separately. These sums, along with the sample size, are used to compute a test statistic which is compared to a critical value or converted to a p-value to determine statistical significance. For example, a researcher could input pre- and post-intervention scores for a group of participants to evaluate the effectiveness of an intervention.
This computational aid offers several advantages in statistical analysis. It reduces the potential for human error in manual calculations, saves time, and allows researchers to focus on interpreting the results. Historically, this type of analysis was performed laboriously by hand using statistical tables. The advent of automated calculation has significantly increased accessibility and ease of use, empowering researchers across various fields to readily apply this method. The utility of the resultant information includes hypothesis validation, data-driven decision-making, and the drawing of meaningful inferences from sample data.
