The mayor's decision to divide the city into 20 different geographic areas to estimate the proportion of households with children can be considered a sampling strategy. This approach is commonly used in statistical surveys to obtain representative data from a larger population while reducing costs.
By dividing the city into geographic areas, the mayor is essentially creating clusters or strata within the population. This stratified sampling approach allows for a more targeted and efficient data collection process. The mayor can then select a sample of households from each geographic area, ensuring representation from different parts of the city.
To estimate the proportion of households with children, the mayor would need to collect data on the presence or absence of children in each sampled household. The sample data collected from the 20 geographic areas can then be used to calculate the proportion of households with children within each area.
Finally, by aggregating the proportions from the 20 different areas, the mayor can estimate the overall proportion of households with children in the entire city. This estimation would be based on the assumption that the selected geographic areas are representative of the city's population as a whole.
It's important to note that the accuracy of the estimate depends on the representativeness of the sampled geographic areas and the sample size within each area. Additionally, proper randomization and sampling techniques should be employed to minimize bias and ensure the reliability of the estimation.