Statistical noise refers to random variations in data that can obscure the true signal or trend. It arises from various sources, such as measurement errors, environmental factors, or inherent variability in the data being collected. This noise can make it challenging to identify meaningful patterns or relationships in statistical analyses. In research, distinguishing between statistical noise and actual effects is crucial for drawing valid conclusions. Techniques like data smoothing or statistical modeling are often employed to minimize the impact of noise, allowing researchers to focus on the underlying trends that are of interest.