Understanding Sampling Variability: Strategies For Accurate Statistical Inferences
Sampling variability arises due to inherent differences between samples drawn from a population, leading to variation in results. Bias, caused by non-random sampling or external factors, introduces systematic variability, while random error refers to unpredictable variations between samples. Understanding sampling variability is crucial for interpreting statistical inferences. Strategies to minimize its effects include using random…