Final answer:
The most appropriate method for conducting a city survey on road repair support is stratified sampling, ensuring all city groups are represented. Random sampling is also suitable, but convenience and snowball sampling could introduce bias.
Step-by-step explanation:
The government of a large city deciding to conduct a survey on whether residents will support the repair of several roads would most appropriately use stratified sampling. This method involves dividing the population into different groups, or strata, and then randomly selecting samples from each of these strata to ensure all groups within the city are represented. For example, the city could be divided into various neighborhoods or districts, and residents from each area would be randomly selected to participate in the survey.
Random sampling would also be an acceptable choice, especially if the city's population is homogenous concerning the issue at hand. Convenience sampling and snowball sampling, however, could lead to biased results and would not be as suitable for this governmental study.
For example, the type of sampling chosen can affect how the collected data represents the city's interests concerning road repairs. Random sampling typically involves a method like a lottery system where each resident has an equal chance of being included, while stratified sampling ensures that specific subgroups within the city are proportionately represented.