- Think about the scientific method that was presented in the introductory video and that can be seen here on screen. First, is asking an interesting research question. Then we want to conduct background research to come up with a theory and a hypothesis. Then we want to collect data to test our hypothesis and report the results. Now, if the evidence refutes our hypothesis, we want to go back and rethink our initial hypothesis and start the process again. As you can tell research questions, theories, and hypothesis are at the center of the scientific method. In this video we will cover how to ask interesting research questions, and develop good theories and hypothesis, so that after watching this video, you should be able to formulate a good research question, identify the components of a good hypothesis, define a theory, and explain the difference between a theory and a hypothesis. The beginning of any scientific endeavor is asking interesting and important research questions. Science is driven by questions. The specific type of question that the scientific method focuses on are called empirical research questions. Empirical research questions, ask about actual events and phenomenon that have occurred or are occurring. These questions are often inspired by puzzling events that we observe in the world and that we learn about in news, documentaries, in books, or elsewhere. As social scientists, we're especially interested in research questions related to social, economic, and political phenomenon. To clarify, empirical research questions don't ask factual questions that have simple correct or incorrect answers. They also don't ask hypothetical questions to ask about some imagined scenario. And they're not normative questions that ask how things should be. Research questions care about more general patterns and phenomena, and go beyond asking about simple facts. To give concrete examples, in this video we will focus on a very timely and important issue in the United States. Police brutality and protests. Think about the recent protests against police brutality in the United States. These protests center around the issue of police officers killing unarmed black people, for example, George Floyd. One of the main actions that these protests call for is for the police officers involved to be investigated, arrested, and prosecuted. This issue raises so many important questions that the United States has to deal with. For example, if the police killed white citizens at the same rate as black citizens, would we see more policy changes? Should the police be defunded? And in what cities did protests against police brutality happen in 2020? However, as important as these questions are, they're not good questions for scientific inquiry. The first is a hypothetical question. The second is a normative question and the third is a factual question. Yet, we can use these interesting questions to rephrase them and create good empirical research questions. For example, are state governments less likely to enact policy changes if an issue only affects minorities? Do the amount of police officers in the city affect the prevalence of police brutality? And why did protests against police brutality happen in some cities and not others? This final question is one we'll use for the remainder of the video. Once we have our research question through our intuition, knowledge, and research, we often have or develop ideas about how to answer our research question. Our proposed answer to a research question is called a theory. Specifically, a theory is a recent and precise speculation about the answer to a research question. For example, if our research question is why did protests against police brutality happen in some cities and not others? We might believe that, or we might answer that protests were more likely to happen in cities that had larger black populations than in cities that have only a small black community. But why might we believe this? Well, one answer you might give is that maybe in cities with a larger black population, there's more community groups and organizations, like a local NAACP chapter, or a local Black Lives Matter chapter that make it easier for the black community to coordinate protests against issues that really affect them. This is an example of a theory. Notice that in our theory, the outcome that I'm interested in is whether a protest happens or not. And the thing that I think might be explaining it is the size of the black population in a city. In scientific language, the outcome that we're interested in is called the dependent variable, because it depends on something else. And the thing affecting or causing the dependent variable we call the independent variable. Good theories are specific and clear about how the independent variable affects or causes the dependent variable. Once we have our theory, we need to derive the testable implications of that theory. But what does that mean? It means that we need to determine the punchline of our theory so that we can test it with data. This testable implication is a hypothesis. Formally, a hypothesis is a statement of the relationship that you expect to find between the dependent variable and the independent variable. For example, take our theory about the size of the black community in the city and protests. We would conclude that following a police brutality case, cities with a larger black population are more likely to experience protests than cities with smaller black populations. This is an example of a hypothesis. This hypothesis follows directly from the theory, and it's a statement that we can then test with data. The general structure of a good hypothesis is the following. As you can see here on the screen, the independent variable leads to the dependent variable. But beyond this very basic structure, what are the components of a good hypothesis? Well, four of the most essential and important components of a good hypothesis are the following. One. It must be specific. It must clearly identify and state the dependent variable and the independent variable. Two. There must be directionality. It must clearly state the direction of the expected relationship between the dependent variable and the independent variable. For example, as the independent variable increases the dependent variable decreases, or the opposite, or a mixture of these. Three. It must be falsifiable. Hypotheses are generalizations that, although we would like to think will always be true, must also be written and structured in a way that evidence could be found that would disconfirm the hypothesis. And four, it must not be immediately verifiable. That is, it must be a general statement and not a factual statement that could be proven true or false with a limited investigation. And just like research questions, a good hypothesis should not be factual, normative, or hypothetical. Hypotheses are tricky because we want them to be general enough to not be immediately verifiable, but we also want them to be specific and clear. Consider this hypothesis. Police brutality cases are linked to police reform. Well, it's specific because we see the independent and the dependent variable, but there's no directionality. We don't know how these two variables are linked. Now, consider this other hypothesis. In Louisville, Kentucky, the murder of Breonna Taylor by the police led to police reform. Well, this is immediately verifiable. We can quickly go online and find out that in fact, yes the murder of Breonna Taylor led to some police reform in Louisville. However, a better way to state these hypotheses or the ideas behind these hypotheses is the following. Police brutality cases are more likely to lead to police reform when protests against the cases take place. We have developed our theories and hypothesis now stemming from our research question. What now? Well, ideally we want to gather data on our independent and dependent variable and test our hypothesis. The evidence might support a hypothesis but it also might refute our hypothesis. If the evidence refutes our hypothesis, we want to go back to our theories and hypothesis and rethink them and start the process again. This illustrates what the scientific method strives for. The accumulation of knowledge that allows us to better understand the world around us. So now, to quickly recap what we've learned in this video. We have learned that research questions ask about interesting phenomenon in the world. Hypotheses are statements that tell us how dependent and independent variables are related. And theories explain why we believe that these variables are related in the way that our hypothesis states. You can now feel free to move on to the exercises and quizzes in this module to better nail down your understanding of these concepts.