1: Why Research Methods Matter

• Begin by considering the fundamental purposes of research. Grasp the nature of research as systematic study to understand or explain the world. Learn important distinctions in research, starting with the notions of basic research vs. applied research. Then define exploratory, descriptive, and explanatory research, and their implications, and examine the six steps of the scientific method.

2: Characteristics of Good Research

• Take a thorough look at what distinguishes sound research from unsound research. Study important criteria for good research, useful both for evaluating the research of others and for structuring our own, noting how good research is systematic, objective, empirical, cumulative, and transparent. Also learn in detail how to spot poor research, and about potential pitfalls for researchers.

3: Doing Research Ethically

• Assess the range of ethical considerations—codes, norms, and principles—that apply to doing research. Look first at the history of ethical violations, and regulations that now exist to govern research. Then review three key principles of ethical research. Delve into the matters of personal ethics in research, ethical review boards, and the process of obtaining consent for research.

4: From Topic of Interest to Research Question

• Most research starts with an underlying topic. Examine different ways to select a topic for your research, and practice an exercise for topic selection. Note how it is vital to develop a compelling research question to focus your project, and how good research questions are “unanswered,” appropriate in scope, and empirical. Finally, study five tips for creating good research questions.

5: What’s Already Known? The Literature Review

• Here, discover why a literature review—a study of the scholarly literature related to your topic—is an essential first step in the research process. Take account of the many benefits that a literature review provides, and the dangers of skipping this step. Grasp how to find the scholarly sources you need, how to identify the core findings in the literature, and how to write your findings up.

6: Generating Hypotheses and Theories

• Learn how theories drive research, when they’re needed, and how to develop a theory, looking first at the literature. Then see how hypotheses function as testable statements that suggest an answer to your research question, and how theory and hypothesis closely intersect. Study four rules for writing a good hypothesis, and work with templates for writing hypotheses that follow these rules.

7: Selecting a Research Design

• This lecture explores a range of approaches to research design, and how to choose one that is best for your project. First, examine both quantitative and qualitative research methods, from experiments and surveys to case studies and field research. Then study key considerations for research design, and see how different kinds of research questions lend themselves to specific methodologies.

8: Measuring Concepts and Phenomena

• Grasp how sound research rests on the ability to measure the variables within your research study. Learn how to conceptually define your variables of interest, and how to “operationalize” and measure your variables prior to data collection. Look at four main levels of measurement, the need for precise data, and the importance of reliability and validity in your measurements.

9: Choosing Populations, Samples, and Cases

• For your research design, investigate the population of cases or data points that apply to your project, and the sample or subset of this population that you will actually study. Delve into key issues in sampling, and learn to define the size of the sample you need. Finally, see how to determine which cases make it into your sample, and review two broad approaches to sampling.

10: The Classic Experiment

• Look deeply into the procedure of the classic or “true” experiment, the hallmark of good scientific research. Study the four requirements or features of a true experiment, and consider the two types of validity that apply to experiments: internal validity and external validity. Then, review the three most common designs for a true experiment, and how they function in practice.

11: The Value of Quasi Experiments

• Refine your understanding of the classic experiment by studying alternative research designs that are closely related. Observe the example of an impactful research study that did not fulfill the full requirements of a true experiment. Dig into the broad category of quasi-experimental designs which, though they fall short of the classic experiment, can still produce very valuable research.

12: Designing and Conducting a Survey

• In the first of two lectures on surveys, observe how surveys are used to find out about peoples’ opinions and behaviors. Look at the various kinds of surveys, which sorts of projects are most suitable for surveys, and evaluate the costs and benefits of different types of surveys. Then learn how to write a survey, highlighting five important principles for creating effective survey questions.

13: Understanding Election Polls

• Focus now on election polling. First, delineate the critical difference between scientific and unscientific polling, and why scientific polling is much more reliable. Study five rules for good polling, which help us evaluate which polls we can trust. Apply these rules to the 2016 U.S. presidential election, and gain insight into why the polling did not match the election results.

14: Research by Case Study

• Case studies examine either one or a small number of cases, with the goal of in-depth understanding of their complexities. Take account of the wide range of uses of case studies in research, and when a case study is a good choice. Learn how case studies make use of multiple types and sources of data, and consider five categories of cases that lend themselves to the case study approach.

15: Interpretivism and Field Research

• Learn how the “interpretivist” approach to research differs substantially from the “positivist” approach we’ve studied so far, highlighting subjective interpretation as opposed to positivism’s search for objective, rational truths. See how the interpretivist approach is applied to field research, and delve into the use of interviews and observation as methods of gathering qualitative data.

16: Applied, Evaluative, and Action Research

• Explore “applied” research, which aims at applying knowledge to problem-solving. First study evaluation research, typically used to evaluate actions or programs in business and government. Then learn about action research, which seeks collaborative solutions to real-world problems, and how to do it. Look also at market and product research, used to determine what consumers want.

17: Gathering and Preparing Data

• Take stock of the kinds of data we’ve looked at, such as data from experiments, interviews, surveys, observation, and the written record. Learn how to put your data into a practical format—most often, using a spreadsheet. Then study coding, the process of transforming raw data into usable categories. Then, look at data analysis programs you can use to help process and analyze your data.

18: Using Statistics to Interpret Data

• Descriptive statistics are simple calculations that help us describe and understand our data. Learn how to use the three calculations of central tendency, which shows us the middle or center of our data, variation, showing how much variation there is in the data, and frequency, which shows how frequently each value appears. Note how the use of “z scores” gives further insights into your data.

19: Statistical Inferences from Data

• Inferential statistics allows us to make inferences and draw conclusions from our data. Begin by studying some key principles for interpreting the implications of your findings. Then review three tests that researchers use to analyze their data and get answers: “Z tests,” “T tests,” and the ANOVA test, which are commonly used to compare statistical differences between groups.

20: Assessing Correlation and Causation

• For your data analysis, study correlation, the relationship or association between two or more variables, and causation, the idea that a change in one variable causes a change in another. Learn how to identify whether a correlation exists between your variables, and to distinguish the form and strength of that relationship. Note that establishing correlation does not establish causation.

21: From Bivariate to Multivariate Analysis

• In this final lesson on quantitative analysis, study three important analytic tools: cross-tabulation tables, which allow us to visually examine the relationship between two variables; chi-squared values, which indicate how likely it is that any pattern or relationship we observe is due to chance; and linear regression, useful in establishing whether one factor or variable causes another.

22: Foundations of Qualitative Analysis

• Begin your study of qualitative methods by noting the differences between quantitative analysis and qualitative analysis, which usually involves identifying patterns and meaning in texts. Explore different scenarios where you may want to use a qualitative approach. Then study one overall, basic approach to qualitative analysis, and see how this approach works in practice.

23: Qualitative Analysis Variations

• Observe how qualitative analysis is less linear than quantitative approaches, and can involve a re-ordering of the steps in the research process. Review several additional qualitative methods, from “grounded theory,” which looks at the implications of core concepts embedded in data, to methods used to interpret texts, conversations, personal narratives, policy, and decision-making.

24: The Art of Presenting Your Findings

• As a final step in the research process, review the range of different approaches to sharing and communicating your findings, from formal to less formal. Take a detailed look at the structure and contents of a formal research report presenting your results, as well as the matters of peer review and the assessment of your work. Conclude with thoughts on the nature and goals of research.

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