Research Methods Flashcards
Steps Involved in Research
- Identify the research problem:
literature search, formulate aim. - Construct research hypothesis
- Design the method: participants, type of experimental design.
- Collect the data: type of data
- Analyse the data: descriptive
statistics - Interpret the data: inferential statistics, conclusions, generalisations.
- Report the research findings:
publish findings
Hypothesis
Testable prediction about the results of a study.
Research Hypothesis
Must include:
1. Population
2. IV (simple)
3. DV (simple)
4. Prediction (direction)
Experiment
Used to test a cause-effect relationship between variables under
controlled conditions.
Advantage:
Conducted under controlled conditions hence reducing EV’s
Disadvantage:
Not conducted in ‘normal’ environment or setting- artificiality can be a confound
Independent Variable
Variable that the experimenter systematically manipulates/changes in the experiment.
Dependent Variable
Variable used to observe/ measure the effect of the IV.
Operationalise
Means to explain what each variable is and how it will be measured.
Case Study
Detailed, in depth account of an individual or group. Involves interviews, observations and psychological tests.
Advantage:
Can be used to direct future research
Disadvantage:
Time-consuming and expensive process
Difficult to generalise
Naturalistic Observation
Involves actively watching behaviour in a natural setting.
Advantage:
Can view participants’ normal behaviour
Disadvantage:
Observer bias may occur
Self Reports
Individuals are simply asked to freely express their thoughts by answering questions (verbally or in writing) about a particular object, person, issue or experience.
- Subjective data.
- Qualitative or quantitative data
- Questions may take a variety of formats. E.g. open-ended, likert scale
Eg. A questionnaire/ interview /rating scale
Cross Sectional Studies
Participants of different ages are
investigated at one particular point in
time.
Advantage:
Data is collected only once, so it is less expensive and more time efficient.
Short term commitment, less drop outs
Disadvantage:
Can’t establish cause and effect
relationship
Factors other than age may play a part in results
Repeated Measures
The same group of participants are exposed to both the experimental and control group.
Advantage:
Individual differences highly controlled
Fewer participants are required.
Disadvantages:
Order effects can occur
Participants have to take part in both conditions so ‘drop-outs’ are more likely
Matched Participants
Placing equivalent pairs of participants into the control and experimental group.
Advantage:
Minimises participant differences
Eliminates order effects
Disadvantage:
Pre-testing is time consuming and
therefore expensive.
If one person drops out-so does the data for the ‘pair
Independent Groups
The participants are only exposed to the experimental or control condition.
Advantage:
Time efficient and easy to use
Less chance of drop outs
Disadvantage:
Participant differences not controlled for.
More participants needed than repeated measures.
Population
It is the larger group of research interest from which a sample has been drawn.
Sample
Group of participants selected from a
population of research interest (a subsection).
Representative Sample
Reflects the characteristics of
the larger population.
Sampling
Process of selection participants from a population for a research study.
Convenience Sampling
Selecting participants based on easy
accessibility or availability.
Advantage:
Quick and easy to obtain sample
Disadvantage:
Very unlikely to get a representative sample (biased)
Random Sampling
Every member of a population has an equal chance of being selected for the sample.
Advantage:
If sample is large enough, it provides an unbiased sample of the population
Disadvantage:
Difficult and time-consuming with a large population
Stratified Sampling
Involves dividing the population into groups/strata based on specific categories and then selecting a sample from each strata in the same proportion that they occur in the population.
Advantage:
Likely to get a representative sample (so generalisations can be made)
Disadvantage:
Very time consuming and costly
Random Allocation
A procedure that ensures all participants have an equal chance of
being selected for the experimental and control group.
Experimental Group
Group exposed to the IV.
Control Group
Group that is not exposed to the IV.
Extraneous Variables
Variable other than the IV that causes a change in the DV.
Confounding Variables
Variable other than the IV that has an unwanted systematic effect on the DV.
Placebo Effect
Changes in behaviour caused by the belief that one is receiving some kind of experimental treatment.
Ways to minimise:
Single blind procedure
Order/Practice Effect
When both the control and experimental groups are made up of the same people. It can result in improved or impaired performance (due to practice, boredom, fatigue).
Ways to minimise:
Counterbalancing
Increase the time period b/w the two conditions.
Non-Standardised Instructions and Procedures
The only difference between the E group and C-group should be the IV. Standardised instructions and procedures are essential.
E.g:
- Language used
- Different researchers
- Testing conditions
- Time of day
Individual Differences
Includes memory ability, motivation, mood, gender, ethnicity, personality, prior experience, IQ etc.
Ways to minimise:
Matched-participants or repeated measures design.
Experimenter Effect
Refers to changes in participants’ behaviour that are caused by the unintentional influence of an experimenter, rather than the effect of the IV.
Ways to minimise:
Double blind procedure
Ethics
Ethics: moral principles and standards that guide people in identifying good, desirable or acceptable conduct. Role of ethics committee.
1. Confidentiality
2. Voluntary participation
3. Informed consent
4. Withdrawal rights
5. Deception
6. Debriefing
Use of Animals in Research
Advantages:
- They can show similar responses to
humans
- They have a shorter life expectancy, therefore we can see effects on ageing quicker
- Their gestation period is shorter allowing for studies on genetics to be conducted quicker
Disadvantages:
- You can only see behavioural effects not cognitive
- Animals are different to humans in many ways
- It is difficult to apply findings in animals to humans
Subjective Data
Data collected through observations of behaviour or based on participants’ self-reports.
Based on opinion, so biased.
Objective Data
Measured according to identifiable criteria.
Data usually in numerical form.
Primary Data
Data collected directly by the researcher for their own purpose, to test a hypothesis.
E.g. Collecting data for your
research investigation
Secondary Data
Data that has been collected by someone other than the original user for their own purpose.
E.g. Accessing data from a journal
Descriptive Statistics
Used to analyse, organise, summarise and describe the results.
E.g:
- Tables
- Graphs
- Measures of central tendency
- Variability (range and standard deviation)
Measures of Central Tendency
- Mean
- Median
- Mode
Mean
Add up all scores and divide result by total number of scores.
Median
Arrange scores from lowest to highest and select middle score.
Mode
Most frequent score.
Measures of Variability
- Range
- Standard Deviation
Range
The difference between the highest and lowest scores in a distribution.
Standard Deviation
Measures the spread of scores around the mean. The higher the standard deviation, the greater the range of values within the sample.
Inferential Statistics
Mathematical calculations that allow us to interpret the data and determine whether the results are meaningful or not.
Allows us to determine if the results support the hypothesis and whether we can draw conclusions.
Conclusion
An inference as to whether the hypothesis has been supported or rejected. NEVER ‘proven’ or ‘disproven’.
Consider:
- CV’s
- Inferential statistics
Generalisations
A statement that relates the findings of the investigation to the wider population.
Consider:
- Obvious flaws of the experiment (CVs)
- Sampling procedure used
- Is the sample size is large enough
- Inferential statistics
Validity
Refers to the extent to which a study measures what it is supposed to measure.
Reliability
Refers to the extent to which results obtained from a study are consistent.
