What is the difference between Statistical significance and Practical significance?

Statistical significance shows the mathematical likelihood that a relationship in the middle of two or more variables exist, while practical relevance refers to the relationship between variables with real-world applications. Statistical significance refers to a lesser chance of sampling error affecting the mean difference.

Statistical signature comes from within data used and confidence of the analyst in the result. Statistical significance hints that a probability of having a relationship exist between the two variables, whereas practical significance implies that existence of a connection between the variables and real-world scenario.

When you are given a mathematical probability question, you might see that there is significance by either being statistical significance or practical significance. Besides both being in mathematical problems, they have differences between them based on their definition and what they have to do with the math problem. Statistical significance refers to the connection among variables that do take place between these variables.

Practical significance relates to connections between variables, but they take place in realistic situations. They do rely on one another to take place. The reason for having practical significance is because it allows people to see how meaningful the information is when they are experiencing real problems in the real world, and math is needed to solve them.