Introduction
Statistical significance is a concept critical to the analysis of data and the interpretation of results. Put simply, it refers to the probability that an observed relationship between two variables is not due to chance. Statistical significance is an important tool for making sense of data and interpreting results, and is used in many scientific fields from the medical sciences to social science.
What Is Statistical Significance?
Statistical significance is a measure of the probability that a relationship between two variables observed in a data set is not due to chance. It is used to determine whether an observed relationship is statistically meaningful or not. Statistical significance is measured by a statistic known as a p-value, which is a number between 0 and 1 that shows the likelihood that the observed relationship could have occurred by chance. Specifically, a p-value of 0.05 (5%) or less indicates that the relationship is statistically significant, and that it is unlikely to have occurred by chance.
Why Is Statistical Significance Important?
Statistical significance is important because it allows researchers to determine whether or not their results are meaningful. Without an understanding of statistical significance, it is difficult to accurately interpret data and draw meaningful conclusions. In addition, statistical significance helps to determine whether an observed pattern in data is a true effect or simply due to random chance. It is also important in reporting research results, as it allows researchers to demonstrate that their findings are statistically meaningful and are likely to occur again if the experiment were repeated.
Who Uses Statistical Significance?
Statistical significance is used in many scientific fields, including biology, medicine and social science. Statistical significance is used to determine whether an observed effect or pattern is likely to be due to chance or if it is likely to be a real phenomenon. In the medical sciences, statistical significance helps to determine whether an observed effect is due to a drug or treatment or simply a random occurrence. In social science, it allows researchers to determine if a relationship between two variables is real or could be due to chance. In general, statistical significance is used in any scientific field where data needs to be analyzed and interpreted.