# 7.3: Unit of analysis and unit of observation

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Learning Objectives

• Define units of analysis and units of observation, and describe the two common errors people make when they confuse the two

Another point to consider when designing a research project, and which might differ slightly in qualitative and quantitative studies, has to do with units of analysis and units of observation. These two items concern what you, the researcher, actually observe in the course of your data collection and what you hope to be able to say about those observations. A unit of analysis is the entity that you wish to be able to say something about at the end of your study, probably what you’d consider to be the main focus of your study. A unit of observation is the item (or items) that you actually observe, measure, or collect in the course of trying to learn something about your unit of analysis.

In a given study, the unit of observation might be the same as the unit of analysis, but that is not always the case. For example, a study on electronic gadget addiction may interview undergraduate students (our unit of observation) for the purpose of saying something about undergraduate students (our unit of analysis) and their gadget addiction. Perhaps, if we were investigating gadget addiction in elementary school children (our unit of analysis), we might collect observations from teachers and parents (our units of observation) because younger children may not report their behavior accurately. In this case and many others, units of analysis are not the same as units of observation. What is required, however, is for researchers to be clear about how they define their units of analysis and observation, both to themselves and to their audiences.

If we were to explore which students are most likely to be addicted to their electronic gadgets, our unit of analysis would be individual students. We might mail a survey to students on campus, and our aim would be to classify individuals according to their membership in certain social groups in order to see how membership in those classes correlated with gadget addiction. For example, we might find that majors in new media, men, and students with high socioeconomic status are all more likely than other students to become addicted to their electronic gadgets. Another possibility would be to explore how students’ gadget addictions differ and how are they similar. In this case, we could conduct observations of addicted students and record when, where, why, and how they use their gadgets. In both cases, one using a survey and the other using observations, data are collected from individual students. Thus, the unit of observation in both examples is the individual.

Another common unit of analysis in social science inquiry is groups. Groups of course vary in size, and almost no group is too small or too large to be of interest to social scientists. Families, friendship groups, and group therapy participants are some common examples of micro-level groups examined by social scientists. Employees in an organization, professionals in a particular domain (e.g., chefs, lawyers, social workers), and members of clubs (e.g., Girl Scouts, Rotary, Red Hat Society) are all meso-level groups that social scientists might study. Finally, at the macro-level, social scientists sometimes examine citizens of entire nations or residents of different continents or other regions.

Organizations are yet another potential unit of analysis that social scientists might wish to say something about. Organizations include entities like corporations, colleges and universities, and even nightclubs. At the organization level, a study of students’ electronic gadget addictions might explore how different colleges address the problem of electronic gadget addiction. In this case, our interest lies not in the experience of individual students but instead in the campus-to-campus differences in confronting gadget addictions. A researcher conducting a study of this type might examine schools’ written policies and procedures, so her unit of observation would be documents. However, because she ultimately wishes to describe differences across campuses, the college would be her unit of analysis.

In sum, there are many potential units of analysis that a social worker might examine, but some of the most common units include the following:

• Individuals
• Groups
• Organizations

On the other hand, another mistake to be aware of is reductionism. Reductionism occurs when claims about some higher-level unit of analysis are made based on data from some lower-level unit of analysis. In this case, claims about groups or macro-level phenomena are made based on individual-level data. An example of reductionism can be seen in some descriptions of the civil rights movement. On occasion, people have proclaimed that Rosa Parks started the civil rights movement in the United States by refusing to give up her seat to a white person while on a city bus in Montgomery, Alabama, in December 1955. Although it is true that Parks played an invaluable role in the movement, and that her act of civil disobedience gave others courage to stand up against racist policies, beliefs, and actions, to credit Parks with starting the movement is reductionist. Surely the confluence of many factors, from fights over legalized racial segregation to the Supreme Court’s historic decision to desegregate schools in 1954 to the creation of groups such as the Student Nonviolent Coordinating Committee (to name just a few), contributed to the rise and success of the American civil rights movement. In other words, the movement is attributable to many factors—some social, others political and others economic. Did Parks play a role? Of course she did—and a very important one at that. But did she cause the movement? To say yes would be reductionist.

It would be a mistake to conclude from the preceding discussion that researchers should avoid making any claims whatsoever about data or about relationships between levels of analysis. While it is important to be attentive to the possibility for error in causal reasoning about different levels of analysis, this warning should not prevent you from drawing well-reasoned analytic conclusions from your data. The point is to be cautious and conscientious in making conclusions between levels of analysis. Errors in analysis come from a lack of rigor and deviating from the scientific method.

## Key Takeaways

• A unit of analysis is the item you wish to be able to say something about at the end of your study while a unit of observation is the item that you actually observe.
• When researchers confuse their units of analysis and observation, they may be prone to committing either the ecological fallacy or reductionism.

## Glossary

• Ecological fallacy- claims about one lower-level unit of analysis are made based on data from some higher-level unit of analysis
• Reductionism- when claims about some higher-level unit of analysis are made based on data at some lower-level unit of analysis
• Unit of analysis- entity that a researcher wants to say something about at the end of her study
• Unit of observation- the item that a researcher actually observes, measures, or collects in the course of trying to learn something about her unit of analysis