Sampling bias occurs when the sample population is not representative of the target population, leading to a skewed or unrepresentative sample. In the case of the supermarket survey, sampling bias could have influenced the results by including a disproportionate number of adults who eat more bread than the general population. For instance, imagine the survey was conducted in an area where bread is a staple food, and a higher proportion of adults consume bread compared to other regions. If the supermarket only surveyed people in that area, the sample would be biased towards bread consumers, and the results would overestimate the number of adults who eat bread. Another example could be if the survey was conducted during a promotional event for bread or in a bakery, where consumers are more likely to purchase bread, leading to a higher proportion of bread consumers in the sample. Therefore, if sampling bias occurred in the survey, it could have made it seem like adults eat more bread than in reality by overestimating the proportion of bread consumers in the sample. To avoid sampling bias, the survey should have been conducted in a way that ensures a random and representative sample of the target population. use this as well