Based on evaluation, provide explanation of implications for social change?

Without knowing what two scenarios you selected, we cannot help you specifically evaluate the sample size, evaluate the statements for meaningfulness, critically evaluate the statements for statistical significance, or provide an explanation of the implications for social change.  We can, however, provide information to you about how you can make those evaluations.

Understanding how statistics work, especially in the context of science and social science research, is very important.  That is because you can have studies that seemingly show the same results, but actually contain very different information.  One important component of any type of statistic presented is the size of the sample compared to the size of the population that you are investigating.  The population size looks at the size of the group you are studying.  The sample size is a smaller subset of that population.  The larger and more diverse the population, the larger and more diverse the sample should be. 

Looking at statistical significance involves understanding the sample size, the population size, and what is being studied.  A result is significant if it meets the significance standard set at the beginning of the research.  The results compare your study group and a control group may be statistically significant, but is the difference enough to make a real difference to the people.  That depends on the size of the population you are studying and what you are studying.  A factor that seems 4% more likely to cause cancer is meaningful, but a factor that means a group is 4% more likely to floss before brushing instead of after brushing may not be as meaningful (unless you are selling dental floss).