Final answer:
Having more controls does not necessarily lead to better oversight, as the efficiency of controls depends on their quality and relevance. Dillon's Rule actually limits local government autonomy, the necessary and proper clause expands federal power, and term limits do not guarantee more women in legislatures. Experimental controls are vital for isolating independent variables in scientific experiments.
Step-by-step explanation:
Having more controls in place does not necessarily guarantee better control. While it may seem intuitive that increasing controls would result in greater oversight and regulation, this is not always the case. In many instances, too many controls can lead to complexity, inefficiency, or even conflict. Moreover, the effectiveness of controls depends on their quality, relevance, and the context in which they are applied, not just their quantity.
For example, consider the statement, "Dillon's Rule gives local governments the freedom and flexibility to make decisions for themselves." The accurate answer is False. Dillon's Rule is a legal principle that states local governments only have the powers expressly granted to them by the state government, thus limiting their autonomy.
Regarding the necessary and proper clause in the Constitution, its effect has been to expand the power of the national government, not limit it, as it allows the government to pass laws deemed necessary and proper for carrying out its enumerated powers. So, the correct answer here is False.
It is also False that term limits have produced a statistically significant increase in the number of women serving in state legislatures. Though the theory is that term limits may open up more opportunities for new candidates, including women, this outcome is not guaranteed.
Lastly, regarding experimental controls, the correct answer is d, which states that "Experimental controls allow comparison between groups that are different in only one independent variable." This method is crucial for establishing cause and effect relationships in experiments.