Question
Which of the following methods is most effective in
reducing selection bias during the sampling process?Solution
Explanation: Selection bias occurs when certain segments of the population are over- or under-represented in the sample. Stratified sampling effectively combats this issue by dividing the population into well-defined strata and sampling proportionally from each. This ensures balanced representation, minimizes bias, and provides a clearer reflection of the entire population. This technique is particularly useful in diverse populations, where subgroups may have different characteristics relevant to the analysis. Option A: Convenience sampling often increases selection bias as it does not account for representativeness. Option B: Systematic sampling can reduce bias but may inadvertently introduce patterns if the population is ordered. Option D: Self-selection introduces significant bias as it relies on participant interest, skewing the sample. Option E: Historical data may not be representative of current conditions, leading to bias in conclusions.
What does the following list comprehension produce?
result = [x**2 for x in range(5) if x % 2 == 0]
print(result)
In Python, which of the following functions in the Pandas library is used to merge two DataFrames df1 and df2 on a common column id?
Which of the following is the main characteristic that differentiates random sampling from non-random sampling techniques?
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Which sampling technique is most suitable when a population has distinct subgroups that should be represented proportionally?
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