Research Methods

• Non-experimental methods

  Observations are a non experimental method of investigation. This means that there is no manipulation of variables, and so observations are not technically classed as experiments. A researcher will simply observe behaviour, and look for patterns. Like all non-experimental methods, in an observation we cannot draw cause and effect relationships. Observations are used in psychological research in one of two ways, a method or a technique within another research method.
• Naturalistic

  In a naturalistic observation, behaviour is studied in a natural situation where everything has been left as it normally is
• Structured /Controlled

  Staged observations, normally carried out within an environment in which the experimenter has some control, such as a lab. Behaviours are usually observed behind a one-way screen. (usually structured)
• Behavioral categories (Coding system)

  -Target behaviour broken into a behaviour checklist

  E.g. a target behaviour of ‘affection’ may be broken down to categories such as hugging, kissing, holding hands etc.

  -Data produced likely to be numerical (quantitative) as the research will tally each time the behaviour is observed
• Sampling Procedures - Continuous

  When all instances of a target behaviour are recorded (typically in unstructured- write down everything seen), (this is not practical/feasible (too much data to record)
• Sampling Procedures - Event sampling


  Counting each time a particular behaviour (or ‘event’) is observed (useful if target behaviour happens infrequently but if

  event is too complex observer may overlook important details)
• Time sampling

  Recording data at particular intervals (reduces the number of observations that have to be made but may miss target behaviors in-between time intervals- findings would be less valid)
• Participant

  An observation where the observer is also a participant (part of the research situation) e.g. researcher studying people in the workplace joins in the workforce
• Non-participant

  An observation where the observer is not part of the situation- remains separate from those being observed
• Overt 


  The person being observed is aware that they are being observed
• Covert

  The person being observed is unaware that they are being observed.
• An example of a coding system

  The Facial Action Coding System (FACS) is used for observing facial expressions. Using the FACS, tally each time your partner shows a particular facial movement
• Dealing with reliability in observations

  • In observational research, the issue is that any observations should be consistent. If they are consistent, we would expect two observers to produce exactly the same observations. The extent to which any two or more observers agree is called inter-rater reliability. This is calculated by correlating the observations of two or more observers. Generally, if there is more than 80% agreement between the observers, the data has inter-observer reliability.
  • Reliability can also be increased by training the observers in the use of a coding system through practice.
• Dealing with validity in observations

  • A researcher can assess the validity of his observations by conducting further observations in different settings with varied people so that the results can be more generalisable.
  • By using more than one observer, observer bias can be reduced.
  • Observer bias can also be reduced by using a double blind technique, where the person doing the observing does not know the aims of the study.
  • The validity of a coding system can be assessed through content, construct, concurrent and predictive methods (see handout on “Validity and Reliability” for a full explanation of these various terms)
• What is content analysis?

  This is a method used to analyse qualitative data (text) by turning it into quantitative data. It is different from an observation as it deals with the content of documents/texts, whereas observations involve looking at the thing that is being studied and recording data.
• How to Conduct a Content Analysis

  1. The researcher chooses the research question 
  2. They select a sample of pre-existing qualitative research (some of which they may have conducted; some of which will have been conducted by other researchers) e.g. interview transcripts, diaries, video recordings, images
  3. The researcher will decide on categories in advance 
  4. The researcher works through the data creating a tally or count the number of times that each of these categories occurs which indicates the categories/codes that are most common in the qualitative data

  • Inter-rater reliability: A second rater conducts the content analysis with the same coding categories and data and compares them; if the results are similar then this shows good inter-rater reliability 
• Falsification

   for something to be scientific it must be able to be proven false. If things are falsifiable (able to possibly be proven false) then they can be used in scientific studies and inquiry. 
• Empiricism

  The idea that knowledge should be gained through experience, i.e. empirically, turned into a method of inquiry that used careful observation and experiments to gather facts and evidence. The nature of scientific inquiry may be thought of at two levels:

  1. that to do with theory and the foundation of hypotheses.

  2. and actual empirical methods of inquiry (i.e. experiments, observations)
• The Key Features of a Science - Empirical Evidence

  Refers to data being collected through direct observation or experiment. Empirical evidence does not rely on argument or belief. Instead, experiments and observations are carried out carefully and reported in detail so that other investigators can repeat and attempt to verify the work.
• The Key Features of a Science - Objectivity

  Researchers should remain totally value free when studying; they should try to remain totally unbiased in their investigations. I.e. Researchers are not influenced by personal feelings and experiences.
• The Key Features of a Science - Control

  All extraneous variables need to be controlled in order to be able to establish cause (IV) and effect (DV).
• The Key Features of a Science - Predictability

  We should be aiming to be able to predict future behaviour from the findings of our research.
• The Key Features of a Science - Hypothesis testing

  E.g. a statement made at the beginning of an investigation that serves as a prediction and is derived from a theory. There are different types of hypotheses (null and alternative), which need to be stated in a form that can be tested (i.e. operationalized and unambiguous).
• The Key Features of a Science - Replication

  This refers to whether a particular method and finding can be repeated with different/same people and/or on different occasions, to see if the results are similar. If a dramatic discovery is reported, but it cannot be replicated by other scientists it will not be accepted. If we get the same results over and over again under the same conditions, we can be sure of their accuracy beyond reasonable doubt. This gives us confidence that the results are reliable and can be used to build up a body of knowledge or a theory: vital in establishing a scientific theory.
• Something it considered unscientific when it:

  -is subjective (involves interpretation)

  -is not measurable/deals with qualitative data

  -has few controls

  -works with an aim and not a hypothesis (‘perhaps’)

  -lacks reliability/credibility