Hi team, Although most city planning officials would consider any drop in local unemployment rate as a good thing, we have to consider the context, sample size, and confidence interval of this situation to measure the actual significance of the drop. When considering the sample and statistical inference, the textbook explains the importance of selecting a random sample to establish an estimation of population parameters. In other words, what is the sample size of the population being measured for unemployment? It is impractical to measure the unemployment status of every individual in the given population, so we must rely on random sampling. In regards to sampling error and confidence intervals, one way to measure significance is to establish a margin of error by taking two random samples of the population and then comparing the unemployment rate from the two samples. We must establish population parameters and leverage random sampling to determine whether or not the unemployment rating has dropped significantly or not. Regardless, it is more important to monitor the trend over time to measure its consistency. Or if it is consistent or not