Research Methods

    Cards (31)

    • Experimental Methods
      The researcher manipulates one or more variables to see how affect other variable. Research has an influence and is able to interfere.
    • Non-experimental methods
      The researcher does not manipulate variables, but instead observes and studies them in their natural environment.
    • Qualitative data
      A type of data that describes characteristics or qualities of something, and is not represented by numbers non-numerical.
    • Quantitative data 
      Data that can be counted or measured in numerical values.
    • Independent variable
      Variable that can be manipulated (changed) by the experimenter.
    • Dependent variable
      The variable which is measured by the experimenter.
    • Lab experiment
      A research method where a researcher intentionally changes a variable to see how it affects another variable in a controlled environment.
      E.g. a university lab
    • Field experiment
      IV is manipulated by researcher, takes place in a real-world setting.
    • Natural experiment
      A research method that involves observing a natural situation as it unfolds, without manipulating, researcher takes advantage of a pre-existing IV.
      E.g. naturally hit by a car
    • Quasi experiment
      Participant are usually observed in their natural environment before and after an intervention. Aims to establish a cause-and-effect relationship between variables.
    • Directional hypothesis (one-tailed)

      Use this when fairly certain of outcome due to prior research.
      E.g. loud noise will significantly reduce a persons ability to read.
    • Non-directional hypothesis (two-tailed)

      Use if are unsure of the directions of results as no prior research.
      E.g. loud noise will have a significant effect on a persons ability to read.
    • Operationalism
      When a variable is defined by the researcher and a way of measuring that variable is developed for the research.
    • Extraneous variable
      A factor which can affect the results of a research study, but is not being investigated.
      E.g. age, gender, or environmental factors, like noise or lighting.
    • Confounding variable
      Something that potentially affects the results of a study but is not accounted for in the study itself.
      E.g. some people may have drink more caffeine throughout the day.
    • Mundane realism (everyday realism)

      a measure of how closely a research study resembles real life.
    • Situational variable
      A factor in the environment that can affect a participants performance.
    • Participant variable
      A characteristics of a participants in a study that could affect the results of the experiment, even though its not the main focus of the study.
    • Investigator variable
      The experimenter unconsciously conveys to participants how they should behave.
    • Demand characteristics
      Cues that may indicate the purpose of an experiment to participants, which can lead them to change their behaviour.
    • Pilot study
      A small-scale, preliminary (done ahead of time) study that is conducted before a larger more comprehensive study.
    • Null hypothesis
      A statement that there is no relationship between two variables being studied, and that any differences observed are due to chance.
    • How do you write a hypothesis?

      Phrase it using an if - then format.
      E.g. if I water a plant every day, then it will grow.
      Predict a relationship between an independent and dependent variable. It is a statement about the expected outcome of a study.
    • What are the steps to writing an operationalised hypothesis?

      ...
    • Single-blind trials
      Participants are unaware of which study group they are in but researchers know.
    • Double- blind trials
      Neither participants nor researchers know what group they are in to prevent bias.
    • Placebo
      An inactive substance or other intervention that looks the same as and is given the same way as an active drug or treatment being tested.
    • Randomisation
      The process of assigning participants to treatment and control groups, assuming that each participants has an equal chance of being assigned to any group.
    • Standardisation
      Keeping everything the same for all participants so that the investigation is fair.
    • Opportunity sampling (pros and cons)
      a sampling technique that involves selecting participants for a study based on their availability and willingness to take part.
      E.g. ask members of the population of interest if they would participate in your research.
      + Quick and easy to access a sample
      -Sample may not be representative of the target population
      -Findings may not be generalisable
    • Random sampling (pros and cons)

      A type of probability sampling in which the researcher randomly selects a subset (a part of a larger group) of participants from a population.
      E.g. lottery or random number method.
      +Lack of bias
      +Simple and quick to select sample
      -The sample may not truly reflect the target market
      -May be expensive as a large sample is required
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