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Research Methods

All key terms from Research Methods

TermDefinition
Levels of the independent variable The different conditions in the experiment
Objectivity Remaining impartial and not biased
Replicability When an experiment or investigation can be repeated multiple times (and by others) with the same findings
Empiricism Gathering actual evidence for the theory
Falsifiability Being able to give a scenario in which the theory could be proved wrong
Hypothesis testing Creating a clear testable statement and then comparing it to experiment
Theory construction Creating a general explanation or model for a specific phenomenon which can be tested
Paradigm A set of assumptions shared by the majority of people in a scientific field
Paradigm shift A significant change to the agreed upon set of assumptions, such as the finding that the Earth orbits the sun rather than the other way around
Quantitative Data Information in the form of numbers
Qualitative Data Information which is not in the form of numbers; e.g. in text
Quasi experiment A study involving an independent variable which has already occurred, where the IV is a characteristic
Laboratory Experiment A controlled study carried out in an artificial setting
Field Experiment A controlled study carried out in a natural setting
Natural Experiment A study involving an independent variable which has already occurred, where the IV is an experience
Correlational Analysis A test of the relationship between two continuous variables, usually plotted on a scattergram
Observation Research which involves directly recording the behaviour of participants (can be natural/controlled, participant/non-participant, and overt/covert)
Self-Report Techniques Research methods whereby the participants provide the information about themselves
Questionnaire Self-report method where participants are given a written set of questions to answer
Open question Where the person responding has freedom over what to say - their choices are not restricted
Closed question Forced-choice questions with limited number of options
Interview Self-report method where participants are usually asked questions face:face
Structured interview Interviews which follow a set list of questions, with no follow-up questions
Unstructured interview Interviews with a theme and topic, but no set questions that allow for elaboration and discussion
Case Study An in-depth analysis of one person or a small group of people
Aims What the research intends to discover
Hypothesis A testable statement - you must operationalise the variables within it
Directional Hypothesis AKA 'one-tailed': A testable statement which predicts that there will be a difference/correlation and can state the direction
Non Directional Hypothesis AKA 'two-tailed': A testable statement which predicts that there will be a difference/correlation but does not state the direction
Null hypothesis A testable statement which predicts that there will be no difference/correlation
Independent Groups Experimental design where participants take part in only one level of the IV
Repeated Measures Experimental design where participants take part in all levels of the IV
Matched Pairs Experimental design where participants take part in only one level of the IV, but are paired with another participant with similar characteristics before being separated into their conditions
Behavioural Categories Coding units used in an observation or content analysis - what the researchers are going to tally
Operationalisation Making variables specific and measurable
Independent Variable (IV) The difference between conditions (what you change)
Dependant Variable (DV) What the researcher measures
Pilot Study A small-scale test carried out before the main study to identify and solve any issues or to make specific decisions
Extraneous Variables (EV) Something has an impact on the DV, which is not the IV
Confounding Variables A third variable which explains a correlation - it changes proportionally with the two other variables
Control Variable A factor that researchers ensure is the same in all conditions to make the study replicable and to avoid extraneous variables
Participant Variables Differences between the people taking part in the study which act as Extraneous variables
Situational Variables Differences between the environments of each condition in the study which act as Extraneous variables
Social Desirability Bias Where participants change their behaviour or answer to make themselves look better
Reliability How consistent the study is
Inter-rater reliability The extent to which different assessors would score the participants in the same way
Test-retest reliability The extent to which the study could be repeated in the same way with the same results
Internal Validity The extent to which the study measures what it claims to measure
External Validity The extent to which the findings can be generalised beyond the study
Population Validity The extent to which the sample can be generalised to the target population
Ecological Validity The extent to which the study can be generalised to realistic settings
Temporal/Historical Validity The extent to which the study can be generalised to modern times
Concurrent validity Whether or not the measure of the IV agrees with a more established measure - e.g. does a person's score correlate with their score on a widely-accepted valid test?
Face validity Whether the measure of the IV seems accurate - usually volunteers are asked to rate its internal validity
BPS Code of Ethics The official guide to ethical issues in Psychology
Deception Ethical issue - Lying to participants
Informed Consent Ethical issue - getting permission from your participants to take part
Protection of Participants Ethical issue - must ensure participants suffer no damage from the study
Right to Withdraw Ethical issue - participants are allowed to leave at any point
Debrief Ethical issue - participants must be told the aim and details of the study at the end
Sampling Techniques Ways in which researchers gather participants
Target Population The group of people who need to be represented by a good sample
Random Sample Sampling method - each person has an equal chance of taking part
Opportunity Sample Sampling method - the people who are in the right place at the right time
Stratified Sample Sampling method - the demographics of the population are reflected in the sample
Systematic Sample Sampling method - list the group and pick every nth person
Volunteer Sample Sampling method - place an advertisement and use the people who select themselves
Demand Characteristics Changes in the participant behaviour due to taking part in the study
Investigator Effects When the researcher has an impact on the outcome
Counterbalancing A method for reducing order effects by ensuring different groups participate in conditions in different orders
Order effects Taking part in one condition affects performance in another condition
Practice effects When you get better in the second condition due to taking part in the first
Fatigue effects When you get worse in the second condition due to taking part in the first
Random Allocation Reducing bias by placing participants in conditions indiscriminately - e.g. by picking names out of a hat
Standardisation Ensuring that the controlled variables are the same in each condition of an experiment - e.g. giving recorded or typed instructions to participants
Scattergram A method of representing correlational data in a visual form
Histogram A method of representing a test of difference where the IV is on a continuous scale (e.g. height)
Bar chart A method of representing a test of difference where the IV is NOT on a continuous scale (e.g. With music/Without music)
Measures of Central Tendency Averages
Mean Adding up all scores and dividing by how many scores there are
Median The middle value
Mode The most common value
Measures of Dispersion Ways of seeing how spread out the data is
Range The highest value - the lowest value
Standard Deviation A measure of how spread out the data are, by finding the average difference from the mean
Positive Correlation As one variable increases, so does the other
Negative Correlation As one variable increases, the other decreases
Correlation Coefficients A measure of the relationship between variables, ranging from -1 to 1. It is the calculated value of a Spearman's rho or Pearson's r test
Content Analysis A method of turning qualitative data into quantitative data by establishing coding units and tallying their occurrence
Thematic analysis When a researcher reviews qualitative data and records recurring patterns or motifs - they do not tally their occurrences however
Peer review A scientific process whereby other scientists check work before it is published
Normal distribution When the mean, median and mode are the same
Positively skewed distribution When the mean is higher than the median and the mode
Negatively skewed distribution When the mean is lower than the median and the mode
Abstract Appears at the beginning of a scientific journal. Summarises the entire study, including aim, method, results and conclusions
Introduction Scientific report section which explains key terms and previous research to justify the current study
Method Scientific report section which outlines the participants, materials and procedure
Results Scientific report section which outlines the raw data from the study, with some descriptive and inferential statistical analysis
Discussion Scientific report section which includes the conclusions and some evaluation of the research, with recommendations for future research
References List of sources used in a scientific report
Descriptive statistics Ways of analysing data that give more information about patterns in the data, e.g. averages, percentages, ratios etc.
Level of measurement Whether the DV is nominal, ordinal or interval
Nominal data Category data without a numeric value (e.g. hair colour)
Ordinal data Level of measurement where there is a scale containing unequal gaps (data may be ranked, subjective or otherwise not equal in gap size)
Interval data Level of measurement where there is a scale containing equal gaps (e.g. height in cm)
Inferential statistics A way of analysing data to determine the likelihood that any difference/correlation is statistically significant
Statistical significance Suggests that results are not due to chance - or it is extremely unlikely they are
p Value The probability that results were due to a chance result. In psychology we accept 5% (or 0.05)
Type I error A false positive - When the alternate hypothesis is accepted incorrectly and the null hypothesis rejected incorrectly
Type II error A false negative - When the alternate hypothesis is rejected incorrectly and the null hypothesis is accepted incorrectly
Calculated value The result of an inferential statistical test
Critical value The number in a data table that you must compare with your calculated value
Related design An experimental design where the participants in one condition are similar to those in another - either repeated measures or matched pairs
Unrelated design Independent groups design - the participants in one condition are not similar or related to those in the other condition
Test of difference A comparison between conditions
Test of association An investigation into a correlation or relationship between co-variables
Created by: SBlakeley
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