10 min read
This study guide covers bias in data collection, focusing on how it can skew statistical studies. It examines various types of bias including voluntary response, undercoverage, nonresponse, question wording, and convenience sampling. Examples and practice problems illustrate how to identify and mitigate these biases, emphasizing their importance for accurate data analysis. A practice question and scoring guidelines are provided.
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Question 1 of 12
What does it mean for a statistical study to be biased? 🤔
It accurately reflects the population being studied
It is likely to underestimate or overestimate the value you are looking for
It is conducted by a large group of researchers
It uses a random sampling method