Solution

Reducing sampling bias requires giving each population member an equal probability of being selected, a hallmark of random sampling techniques. This approach minimizes the likelihood of overrepresenting or underrepresenting certain groups within the sample, resulting in more reliable and accurate findings. By using unbiased sampling methods, analysts can ensure that the sample better reflects the population, leading to more generalizable results. Option A is incorrect because selecting the easiest data points is a form of convenience sampling, which introduces bias. Option B is incorrect as relying only on historical data may not reflect current or future trends, leading to bias. Option D is incorrect because selecting data that aligns with a hypothesis introduces confirmation bias. Option E is incorrect since samples from a single location may not represent a diverse population, leading to geographic bias.