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All key terms from Research Methods

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