Final answer:
Cherry-picking data is the selective use of data points that confirm a certain view, ignoring contradicting data. Spotting it involves checking for biases, verifying evidence, and considering statistics like sample size and margin of error. Everyday examples include selecting news stories that align with one's own beliefs.
Step-by-step explanation:
Cherry-picking data refers to the act of selectively choosing data points that support a particular view or argument, while ignoring data points that might contradict it. This practice can be observed in many spheres of society, from the media to political candidates, and it affects how decisions are made, including what goes into legislation.
To identify cherry-picking, one must critically analyze where the information comes from, examine the evidence used to support it, check for reproducibility of results, and be aware of biases. Question elements such as the sample size, margin of error, clarity of the questions, and how recently the data was collected. Reputable polling organizations often provide these details to demonstrate scientific reliability. It's important to verify if the data is representative and randomly sampled, which contributes to its credibility.
Furthermore, cherry-picking can manifest in everyday situations, such as a person only reading news stories that align with their pre-existing beliefs. Spotting cherry-picking requires a keen eye for detail, an understanding of statistical analysis, and skepticism of partial information.