Quantitative Methods Questions
Statistical significance in hypothesis testing refers to the likelihood that the observed results are not due to chance or random variation. It is a measure of the strength of evidence against the null hypothesis, which assumes that there is no relationship or difference between variables. A statistically significant result indicates that there is a low probability that the observed outcome occurred by chance alone, suggesting that there is a true relationship or difference between the variables being tested. The level of statistical significance is typically determined by comparing the p-value (probability value) to a predetermined threshold, often set at 0.05 or 0.01. If the p-value is below the threshold, the result is considered statistically significant, and the null hypothesis is rejected in favor of the alternative hypothesis.