Research methods

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dependent variable
The experimental factor that is manipulated
the thing that is measured
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One-tailed hypothesis (directional)
Two tailed hypotheses (non directional)
Predicts a specific direction of results
does not predict a specific direction
a general statement that no things affect each other
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Null hypotheses
Predicts a specific direction of results
does not predict a specific direction
a general statement that no things affect each other
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extraneous variable
In an experiment, a variable other than the IV that might cause unwanted changes in the DV.
Order effects, demand characteristics, investigator's effect
Situational variables
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Participant variable
Noise, temperature, light
AGe, Gender, attitude, mood
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Controlling Extraneous Variables
randomization, standard procedure, single blind, counterbalancing, double blind
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Lab experiment
An experiment that takes place in a controlled environment where the researcher manipulates the IV and records the effect on the DV while maintaining strict control of extraneous variables.
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Strengths of lab experiments
- control extraneous variables- this creates high internal validity - easier to establish causal relationships
- you can replicate - increases reliability
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Weakness of lab experiment
-Less life like - Low ecological validity - cant be generlised
-Unnatural response - High demand characteristics
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field experiment
an experiment conducted in the participants' natural environment. IV is manipulated and DV measured
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Strengths of field experiments
Behaviour in a field experiment is more likely to reflect real life because of its natural setting - higher ecological validity
Less likelihood of demand characteristics affecting the results, as participants may not know they are being studied - covert.
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Weaknesses of field experiments
There is less control over extraneous variables that might affect the DV - difficult to establish causal relationship
Replication is difficult - the same conditions can not be recreated - decreasing reliability
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natural experiment
An experiment conducted in a natural environment, IV manipulated by the nature
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S/W of natural experiment
S -Iv is naturally occuring - high ecological validity
No demand characterisitcs - natural environment
W- Cannot control the extraneous variable might affect the DV
Difficult to replicate
Difficult to infer cause and effect
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Experimental designs
Independent groups
Repeated measures
Matched pairs
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Independent groups
Participants are randomly allocated to one condition of the IV. One group undergoes one condition and the other group undergoes another
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S&W: independent groups
S - No order effects, no demand characterisitcs
W - cannot control partcipants variable, double the amount of Ps needed than repeated measure
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Repeated measures
Ps take part in both conditions
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S/W of repeated measures
S- half the no. of Ps needed, redecued Partipant variables
W - Order effects, demand characterisitics
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Matched pairs
Ps matched based on characterisitcs, then each P is allocated to one of the conditions of the IV
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S/W of matched pairs
S - No order effects, reduced demand characterisitcs
W - TIme consuming match Ps, Difficult to reduce all P variables
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Reliability
consistency of measurement
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internal validity
the extent to which the results of a study can be generalized to other situations and to other people
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external validity
extent to which we can generalize findings to real-world settings
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Subjective vs objective
Statements based on personal feelings and/or experiences
statement based on facts, not debatable
Qualitative data
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Quantitative data
descriptive data, rich in detail (interview answers)
numerical data
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S/W of qualitative data
S -allows respondants to explain their answers
W- cannot cross compare with other respondants
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S/W of quantitative
S - present graphs, calculate mean, median, mode, helps draw conclusions
W- does not explain answers
Primary data
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Secondary
data collected by the psychologuist for their own research
Data initially collected by someone else and the psychologist uses for their own purpose
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Correlation designs
Studies that measure two or more variables and their relationship to one another; they are not designed to show causation
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S of correlation designs
S- allows to see if two variables are linked, may prompt further investigation too look for causation using experimental method
Useful when it is unethical or impractical to recreate certain conditions
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W of correlation designs
W - do not tell us how the variable are related, we dont know what causes it
there may be intervening variables - no control of EV
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Case studies
in-depth investigation into an individual or a small group od people
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Strengths of case studies
Provides detailed (rich qualitative) information.
Provides insight for further research.
Permitting investigation of otherwise impractical (or unethical) situations.
COnducted over years - see change in behaviour
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Weaknesses of case studies
-Not a generalisable sample
-Researchers have very little control over variables
-Difficult to establish causal relationships
- Biased - interpreted by researcher
- approval from ethics committee (timely, costly)
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Observational designs
Participants/non particpant/overt/covert
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S/W of observational designs
S -+Obtain true and accurate picture of natural behaviour (high external validity)
W - Difficult to distinguish whether one factor affects the other
-Time consuming and needs constant attention
-Ethical issues as they cannot give informed consent
-Observer bias
-Hard to replicate
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Questionaires
A self report data collection instrument that is filled out by research participants
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types of qs
Closed questions/open questionsraded questions
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Interview
Structurednstructured
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Ethic guidlines
Informed consent
Deception
Right to withdraw
Protection from harm
Debriefing
Confidentiality
Privacy
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Sampling methods
- Random- Opportunity- Volunteer - Stratified
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Graphs and distribution
Scatter graphs - relationship between two co variables
Histograms - represent continous data, no gaps between bars, show frequency
Bar charts - Show categorical data, has gaps
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normal distribution curve
the bell-shaped curve
Mean median mode are similar
data spread out evenly
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Negatively skewed distribution
Long tail extends to the left, most data is high
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Positively skewed distribution
Mean, median not similar, long tail extends to the right, most data is low
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