Statistical Significance
Introduction
Statistical significance is a term used in statistics to denote the likelihood that a relationship between two or more variables is caused by something other than random chance. Statistical significance is often expressed in terms of a P-value, which is the probability that the observed relationship could have occurred by random chance. The lower the P-value, the greater the statistical significance.
Concept and Definition
The concept of statistical significance is fundamental to the process of hypothesis testing in statistics. It is used to determine whether a null hypothesis should be rejected or not. The null hypothesis is a general statement or default position that there is no relationship between two measured phenomena. Rejecting or disproving the null hypothesis—and thus concluding that there are effects present—is a central task in the modern practice of science, and gives a precise sense in which a claim is capable of being proven false.
Calculation of Statistical Significance
Statistical significance is calculated using a test statistic, which is a measure of how far observed data is from being consistent with the null hypothesis. The test statistic is then compared to a critical value, which is a threshold set by the researcher (often at 0.05 or 5%). If the test statistic is more extreme than the critical value, then the null hypothesis is rejected in favor of the alternative hypothesis. This is often interpreted as providing evidence that the data is statistically significant.
Misinterpretations and Misuse
Despite its importance in statistical hypothesis testing, the concept of statistical significance is often misunderstood and misused in scientific research. One common misconception is that a statistically significant result is always of practical significance. However, a statistically significant result merely indicates that it is unlikely that the observed relationship is due to chance; it does not necessarily imply that the relationship is large or important.
Importance in Research
Despite the potential for misuse, statistical significance plays a crucial role in scientific research. It provides a measure of the reliability of the results of a study. By providing a quantifiable measure of uncertainty, statistical significance helps researchers to draw reliable conclusions from their data.