Methods of Collecting Data


Observational studies allow researchers to document behavior in a natural setting and witness events that could not be produced in a lab.

Learning Objectives

Give examples of when observational studies would be advantageous, and when they would have limitations

Key Takeaways

Key Points

  • Observation differs from most other forms of data collection in that the researcher does not manipulate variables or directly question participants.
  • The advantages of observation include observing natural behavior, refining hypotheses, and allowing for observation of behavior that cannot be produced in an artificial environment for ethical or practical reasons.
  • The disadvantages of observation are that these studies do not produce quantitative data, do not allow for cause and effect statements, may be very time consuming, and can be prone to researcher bias.

Key Terms

  • observational research: Research focusing on the observation of behavior outside of a laboratory setting.
  • external validity: In research, whether or not study findings can be generalized to real world scenarios.

Observation allows researchers to experience a specific aspect of social life and get a firsthand look at a trend, institution, or behavior. Participant observation involves the researcher joining a sample of individuals without interfering with that group’s normal activities in order to document their routine behavior or observe them in a natural context. Often researchers in observational studies will try to blend in seamlessly with the sample group to avoid compromising the results of their observations.

Observational research is a type of descriptive research that differs from most other forms of data gathering in that the researcher’s goal is not to manipulate the variables being observed. While participants may or may not be aware of the researchers’ presence, the researchers do not try to control variables (as in an experiment), or ask participants to respond to direct questions (as in an interview or survey based study). Instead, the participants are simply observed in a natural setting, defined as a place in which behavior ordinarily occurs, rather than a place that has been arranged specifically for the purpose of observing the behavior. Unlike correlational and experimental research which use quantitative data, observational studies tend to use qualitative data.

For example, social psychologists Roger Barker and Herbert Wright studied how a sample of children interacted with their daily environments. They observed the children go to school, play with friends, and complete daily chores, and learned a great deal about how children interact with their environments and how their environments shape their character. Similarly, anthropologist Jane Goodall studied the behavior of chimpanzees, taking careful notes on their tool making, family relationships, hunting, and social behavior. Her early work served as the basis for future research on chimpanzees and animal behavior in general.

Advantages of Observational Studies

By observing events as they naturally occur, patterns in behavior will emerge and general questions will become more specific. The hypotheses that result from these observations will guide the researcher in shaping data into results.

One advantage of this type of research is the ability to make on-the-fly adjustments to the initial purpose of a study. These observations also capture behavior that is more natural than behavior occurring in the artificial setting of a lab and that is relatively free of some of the bias seen in survey responses. However, the researcher must be careful not to apply his or her own biases to the interpretation. Researchers may also use this type of data to verify external validity, allowing them to examine whether study findings generalize to real world scenarios.


Laboratory Observation: Laboratory observation can feel artificial to participants and influence their behavior. Observation in a natural setting allows researchers to document behavior without this influence.

There are some areas of study where observational studies are more advantageous than others. This type of research allows for the study of phenomena that may be unethical to control for in a lab, such as verbal abuse between romantic partners. Observation is also particularly advantageous as a cross-cultural reference. By observing people from different cultures in the same setting, it is possible to gain information on cultural differences.

Disadvantages of Observational Studies

While observational studies can generate rich qualitative data, they do not produce quantitative data, and thus mathematical analysis is limited. Researchers also cannot infer causal statements about the situations they observe, meaning that cause and effect cannot be determined. Behavior seen in these studies can only be described, not explained.

There are also ethical concerns related to observing individuals without their consent. One way to avoid this problem is to debrief participants after observing them and to ask for their consent at that time. Overt observation, where the participants are aware of the researcher’s presence, is another option to overcome this problem. However, this tactic does have its drawbacks. When subjects know they are being watched, they may alter their behavior in an attempt to make themselves look more admirable.

This type of research can also be very time consuming. Some studies require dozens of observation sessions lasting for several hours and sometimes involving several researchers. Without the use of multiple researchers, the chances of observer bias increase; because behavior is perceived so subjectively, it is possible that two observers will notice different things or draw different conclusions from the same behavior.

Case Studies

A case study is a method of obtaining in-depth information on a person, group or phenomenon to provide descriptions of specific or rare cases.

Learning Objectives

Evaluate the advantages and disadvantages of using case studies

Key Takeaways

Key Points

  • Case studies allow for the development of novel hypotheses for later testing, provide detailed descriptions of rare events, and can explore the intricacies of existing theories of causation.
  • Case studies cannot directly indicate cause and effect relationships or test hypotheses. In addition, findings from case studies cannot be generalized to a wider population.
  • Famous case studies, like that of Phineas Gage, and researchers using case studies, like Jean Piaget, have helped establish entire fields of psychology. Phineas Gage helped researchers understand the relationship between brain areas and personality, while Piaget developed a model of development based on his studies.

Key Terms

  • psychometric test: The measurement of knowledge, abilities, attitudes, personality traits, and educational measurements.
  • case study: Research performed in detail on a single individual, group, incident or community, as opposed to, for instance, a sample of the whole population.

A case study in psychology is a descriptive research approach used to obtain in-depth information about a person, group, or phenomenon. It is different from survey research, which involves asking a group of participants questions through interviews or questionnaires. Cast studies also tend to be far more in-depth than observational research in that they use multiple measures or records and focus on a single subject. (A multiple-case design can be used in some instances.) Case studies may be prospective or retrospective; prospective studies feature criteria that are established and include additional cases that meet those criteria as they become available, while retrospective studies use criteria to select cases from historical records. Case studies also tend to use qualitative data, such as interviews, but may occasionally use quantitative data as well, like questionnaires. They are often seen in clinical research, where the treatment of a specific individual is monitored to determine what is effective.

Case studies use techniques such as personal interviews, direct observation, psychometric tests, and archival records to gather information. They are used to explore causation in order to find underlying principles. However, they cannot be generalized to the overall population, as can experimental research, and they cannot provide predictive power, as can correlational research. Rather, they can provide extensive information for the development of new hypotheses for future testing, or about a rare or otherwise hard-to-study event or condition. As such, they are often seen in clinical research, where the treatment of a specific individual is monitored to determine what is effective.

For instance, a client in a mental health hospital could be studied as he progresses through a course of treatment involving individual counseling, group therapy and medication. While any results from the study could only be applied to that particular client, the results could inform a future hypothesis about the relative effectiveness of such treatment options.

Techniques Used in Case Studies

The most common techniques used to collect data for case studies are:

  • personal interviews
  • direct observation
  • psychometric tests
  • archival records

Advantages of Case Studies

One major advantage of the case study in psychology is the potential for the development of novel hypotheses for later testing. Case studies are used to explore ideas on a subject and can determine underlying principles. An “average” or “typical” case is often not the richest in terms of information, but with a case study, researchers can choose the most informative subjects to examine in depth. Picking and choosing data like this is impossible in experimental studies. This method can also provide incredibly detailed descriptions of specific and rare or otherwise hard-to-study cases. With rare events, such as specific injuries to the brain or sociopathic behavior, a case study allows for a detailed analysis of the behaviors and situations related to these events which could not be recorded ordinarily. Lastly, this type of research also allows for the observation of phenomenon in real-life situations.

Disadvantages of Case Studies

A researcher cannot draw cause and effect relationships from case studies. Even though a case study may indicate that a specific circumstance is associated with a particular trait or situation, it does not mean that all cases relate to those same factors. Case studies also cannot test hypotheses. While they can gather information to inform hypotheses, they cannot support or refute a prediction. Case studies cannot be generalized to the overall population, as in experimental research, nor can they provide predictive power, as in correlational research. The observations made in a case study are based on a very limited sample, and since this sample is not randomized or typically very large, the findings cannot be extrapolated to apply to broader contexts.

Well-Known Case Studies

Some famous case studies in psychology include:

  • Phineas Gage: Gage was a rail construction foreman who survived an accident in which a tamping rod went through his skull and brain. The injury destroyed most of his frontal cortex, and subsequently had dramatic effects on his personality, therefore informing scientists about the connection between regions of the brain and personality and behavior.
  • Freud and Little Hans: Sigmund Freud completed an extensive case study about a 5-year-old boy he called “Little Hans,” exploring the reason for his phobia of horses.
  • Little Albert: John Watson’s study of classical conditioning in a 9-month-old boy named Albert examined whether it was possible to condition an otherwise emotionally stable child to fear a stimulus that most children would not find fearful.
  • John Money and the John/Joan case: An examination of the impacts of sexual reassignment surgery on David Reimer.
  • Genie: The case study of a child who was raised in total isolation and thought of as “feral.”
  • Jean Piaget’s studies examined phases of cognitive and intellectual development.

Surveys and Interviews

Surveys are a low-cost option for gathering a large amount of data, but they are also susceptible to reporting bias.

Learning Objectives

Evaluate the advantages and disadvantages of using the survey method in psychological research

Key Takeaways

Key Points

  • The survey method of data collection is likely the most common of the four major research methods.
  • The benefits of this method include low cost, large sample size, and efficiency.
  • The major problem with this method is accuracy: since surveys depend on subjects’ motivation, honesty, memory, and ability to respond, they are very susceptible to bias.
  • A researcher must have a strong understanding of how to properly frame survey questions in order to gather reliable and relevant information.

Key Terms

  • reliability: The degree to which a measure is likely to yield consistent results each time it is used.
  • validity: The degree to which a measure is actually assessing the concept it was designed to measure.
  • survey: A method for collecting qualitative and quantitative information about individuals in a population.


Interviews are a type of qualitative data in which the researcher asks questions to elicit facts or statements from the interviewee. Interviews used for research can take several forms:

  • Informal Interview: A more conversational type of interview, no questions are asked and the interviewee is allowed to talk freely.
  • General interview guide approach: Ensures that the same general areas of information are collected from each interviewee. Provides more focus than the conversational approach, but still allows a degree of freedom and adaptability in getting the information from the interviewee.
  • Standardized, open-ended interview: The same open-ended questions are asked to all interviewees. This approach facilitates faster interviews that can be more easily analyzed and compared.
  • Closed, fixed-response interview (Structured): All interviewees are asked the same questions and asked to choose answers from among the same set of alternatives.


The survey method of data collection is a type of descriptive research, and is likely the most common of the major methods. Surveys have limited use for studying actual social behavior but are an excellent way to gain an understanding of an individual’s attitude toward a matter.

Similar to an interview, a survey may use close-ended questions, open-ended questions, or a combination of the two. “Closed-ended questions” are questions that limit the person taking the survey to choose from a set of responses. Multiple choice, check all that apply, and ratings scale questions are all examples of closed-ended questions. “Open-ended questions” are simply questions that allow people to write in their own response.

Surveys are a highly versatile tool in psychology. Although a researcher may choose to only administer a survey to sample of individuals as their entire study, surveys are often used in experimental research as well. For example, a researcher may assign one group of individuals to an experimental condition in which they are asked to focus on all the negative aspects of their week to induce a negative mood, while he assigns another group of people to a control group in which they read a book chapter. After the mood induction, he has both groups fill out a survey about their current emotions. In this example, the mood induction condition is the independent (manipulated) variable, while participants’ responses on the emotion survey is the dependent (measured) variable.

Advantages of Surveys

The benefits of this method include its low cost and its large sample size. Surveys are an efficient way of collecting information from a large sample and are easy to administer compared with an experiment. Surveys are also an excellent way to measure a wide variety of unobservable data, such as stated preferences, traits, beliefs, behaviors, and factual information. It is also relatively simple to use statistical techniques to determine validity, reliability, and statistical significance.

Surveys are flexible in the sense that a wide range of information can be collected. Since surveys are a standardized measure, they are relatively free from several types of errors. Only questions of interest to the researcher are asked, codified, and analyzed. Survey research is also a very affordable option for gathering a large amount of data.

Disadvantages of Surveys

The major issue with this method is its accuracy: since surveys depend on subjects’ motivation, honesty, memory, and ability to respond, they are very susceptible to bias. There can be discrepancies between respondents’ stated opinions and their actual opinions that lead to fundamental inaccuracies in the data. If a participant expects that one answer is more socially acceptable than another, he may be more motivated to report the more acceptable answer than an honest one.

When designing a survey, a researcher must be wary of the wording, format, and sequencing of the questions, all of which can influence how a participant will respond. In particular, a researcher should be concerned with the reliability of their survey. “Reliability” concerns the degree to which the survey questions are likely to yield consistent results each time. A survey is said to have high reliability if it produces similar results each time. For example, a reliable measure of emotion is one that measures emotion the same way each time it is used. However, for a survey to be useful, it needs to be not only reliable, but valid. If a measure is has high “validity”, this means that it is in fact measuring the concept it was designed to measure (in this case, emotion). It is important to note that a survey can be reliable, but not valid (and vice versa). For example, just because our emotion survey is reliable, and provides us with consistent results each time we administer it, does not necessarily mean it is measuring the aspects of emotion we want it to. In this case, our emotion survey is reliable, but not necessarily valid.

Structured surveys, particularly those with closed-ended questions, may have low validity when researching affective variables. Survey samples tend to be self-selected since the the respondents must choose to complete the survey. Surveys are not appropriate for studying complex social phenomena since they do not give a full sense of these processes.

Key Elements of a Successful Survey or Interview

While survey research is one of the most common types of psychological study, it can be difficult to create a survey that is free of bias and that reliably measures the factors it aims to capture. A researcher must have a strong understanding of the basics before they can create a valid survey from scratch. Surveys must be carefully worded and include appropriate response formats. The way a question is written can confuse a participant or bias their response, and poorly framed or ambiguous questions will likely result in meaningless responses with very little value. Questions should be clear, address only one topic at a time, and avoid leading the respondent to a specific answer (in other words, a question should not suggest the correct response in how it is worded). When designing a survey, it is important to understand your audience and use words they will understand and make sure your survey is not too long for them to easily complete.


Survey research books: While survey research is one of the most common types of psychological study, it can be difficult to create a survey that is free of bias and that reliably measures the factors it aims to capture. A researcher must have a strong understanding of the basics before they can create a valid survey from scratch.

Types of Data Gathered in Surveys and Interviews

Surveys may measure either qualitative or quantitative data. Qualitative data are the result of categorizing or describing attributes of a population such as hair color, blood type, or ethnic group. Qualitative data are usually described by words or letters. This type of data does not lend itself to mathematical analysis, but bar graphs and pie charts tend to demonstrate this type of data well.

Quantitative data are always numbers. Quantitative data are the result of counting or measuring attributes of a population, such as money, pulse rate, weight, or populations. This type of data may be either discrete (meaning they take on only certain numerical values, such as the number of phone calls you receive per day or the number of jeans you own—you might have 2 or 3 pairs of jeans, but you cannot have 2.5 pairs) or continuous (data that are the result of measurements such as weight, height, or amount of blood donated). Discrete data use whole numbers, while continuous data utilize decimals and fractions.