What is the main purpose of a sign test in research?

The main purpose of a sign test in research is to determine whether a hypothesis should be accepted or rejected. This statistical test is particularly useful in situations where we are dealing with paired observations or the differences between two groups. It evaluates whether there is a significant difference in the direction of the changes—essentially examining the signs of the differences (positive or negative) without making assumptions about the distribution of the data.

In the context of hypothesis testing, the sign test allows researchers to conclude if the observed differences in data are likely to occur by chance or if they reflect a true effect related to the independent variable being studied. This is particularly important in non-parametric statistics, where traditional parametric tests might not be appropriate due to violations of assumptions such as normality. Therefore, using the sign test helps researchers determine the validity of their null hypothesis more robustly when dealing with ordinal data or when sample sizes are small.