Glossary

data: relatively uninterpreted information received through human senses

descriptive statistics: methods for numerical summary of set of sample data

inferential statistics: methods for assessing the probability of chance occurence of certain data differences or relationships

design: overall structure and strategy of a piece of research

sample: group selected from population for study or experiment

population: all possible members of a group from which a sample is taken

Types of Hypothesis

hypothesis: precise prediction of relationships between data to be measured; usually made to support more general theoretical explanation

alternative hypothesis: precise statement of relationship between data to be measured. the hypothesis tested in a research project. contrasted to the null hypothesis

experimental hypothesis: hypothesis tested in a particular experiment

research hypothesis: hypothesis tested in a particular piece of research

null hypothesis - prediction that the data do not vary in the way which will support the theory under investigation. very often the prediction that differences or correlations are 0

directional hypothesis (one-sided/one-tailed): hypothesis in which the direction of difference or relationship is predicted before testing. example - significantly more people will order chicken than beef

non directional hypothesis (two-sided/two-tailed): hypothesis in which the direction of difference or relationship is not predicted before testing. example - there will be a significant difference in the number of people who order chicken and beef

Types of Variables

confounding variable: variable which is uncontrolled annd obscures any effect sought, usually in a systemic manner

dependent variable: variable which is assumed to be directly affected by changes in the independent variable

independent variable: manipulated variable in an experiment which is assumed to have a direct effect on the dependent variable

extraneous variable: anything other than the IV which could affect the dependent variable. it may or may not have been allowed for and/or controlled.

random variable: a variable that creates unpredictable errors in measurement

participant/subject variables: variables which differ between groups of people and which may need to be controlled in order to demonstrate an effect of the DV

Types of Groups

control group: group which is used as a baseline measure against which the performance of the intervention group is assessed

experiment/treatment group: group who recieves values of the IV in ann experiment or quasi-experiment

placebo group: group who dont recieve treatment but everything else the experimental group recieve and who are sometimes lef to believe their treatment will have an effect

Types of Sampling

cluster sampling: sample selected from a specific area as beinng representative of a population

opportunity sampling: sample selected because they are easily available for testing

systematic sampling: sample selected by taking every nth case

quota sampling: sample selected so that specified group[s will appear in numbers proportional to their size in the target population

random sampling: sample selected in which every member of the target population has an equal chance of being selected

self-selecting sampling: sample selected for study on the basis of their own action in arriving at the sampling point

snowball sampling: sample selected for study by asking key figures for people they think will be important or useful to include

stratified sampling: samples are selected so that specified groups will appear in numbers proportional to their size in the target population, within each subgroup cases are selected on a random basis

Reliability and Validity

reliability: extent to which findings or measures can be repeated with similar results

replication: repetition of a study to check its validity

standardised procedure: way of testing of acquiring measures from participants which is repeated in exactly the same way each time for all common parts of the method

validity: extent to which instruments measure what it is intended to measure

ecological validity: extent to which investigation can be generalised to other places and conditions

external validity: extent to which results of the research can be generalised acorss people, places, times and other measures of the variables

internal validity: extent to which the effect found in a study can be taken to be real and caused by the identified independent variable

Philosophy

experimental realism: effect of attentionn grabbinf, interesting experiment in compensating for artificiality or demand characteristics

mundane realism: effect of research design which resembles everyday life but is not necessarily engaging to participants

positivism: methodological belief thst description of the world’s phenomena is reducvible to observable facts and the mathematical relationships between them

qualitative approach: methodological stance which holds that innformation about human events and experience, if reduced to numerical form, loses most of its important meaning and valiue for research and understanding

qualitative data: information which is not in, or reducible to, numerical form

quantitative data: information gathered which is in, or reduced to, numerical form

Study Design

correlational study: study of the extent to which one variable is related to another, often referring to non-manipulated variables measured outside the laboratory

demand characteristics: features in a study which help the participant work out what is expected of them

double blind: procedure in the experiment where neither participants not data gatherer know which treatment participants have received

evaluation apprehension: participants concerns about being tested which may affect the results

field experiment: experiment carried out in a natural setting outside the laboratory

laboratory experiment: carried out in control conditions inn the experimenters own habitat

natural experiment: experiment which exploits the occurrence of a naturally occurring independent variable

quasi-experiment: experiment in which experimenter does not have control over random allocation of participants to conditions, nor, in some cases, over the independent variable

experimenter expectancy: tendency for experimenter’s knowledge of what is being tested to influence the outcome of research

experimenter reliability: the intent to which the results produced by 2 or more experimenters are related

ex post facto research: research where pre-existinng and non manipulated variables among people are measured for difference or correlation

observational study: research which simply measures characteristics of how people are or behave but doesn’t intervene

pleasing the experimenter: tendency of participants to act in accordance with what they think the experimenter would like

single blind: procedure in an experiment where participants do not know which treatment they have received

social desirability: tendency of participants in research to want to look good and provide socially acceptable answers

counterbalancing: half participants do conditions in particular order and the other half take in the opposite order

independent samples: two or more separate groups take the various conditions of the independent variable

matched pairs: each participant in onne group/condition is paired on specific variables with a participant in another group/condition

repeated measures: each participant takes part in all conditions on the independent variable

Observational Research Methods

content analysis: analysis of content of media sources/descriotions/verbal reports through coding, categorisation and rating

diary method: participant makes regular record of relevant events

disclosure: letting people know that they are the object of observation

event sampling: observation and recording of specific events defined for the study

formative approach: approach to observation in which the focus of the observation may change as the study progresses and early data are analysed

knowledge elicitation: gathering data which is assumed to form the observed person’s knowledge and understanding of a specific system. often using verbal prompts

controlled observation: observation in which many variables are kept constant

indirect observation: observation without intervention in observed people’s own environment

non-participant observation: observation in which observer does not take part or play a role in the group observed

participant observation: observation in which observer takes part or plays a role in the group observed

structured observation: observation which uses an explicitly defined framework for data recording

observational design: study which is solely observational and does not include and experimentation

observational technique: study using observation in some way and which may or may not be an experiment

observer bias: effect causing unwanted variations in data recorded which are produced because of characteristics of the observer

inter-rater reliability: extent to which observers agree in their rating or coding

point sampling: observation of one person long enough to record one category of behaviour before moving on to next individual to be observed

rating: assessment of behaviour observed by choosing a point along a scale

roleplay: study in which participants act out parts

simulation: study in which participants recreate and play through, to some extent, a complete social settig

time sampling: observation of individuals for set lengths of time

verbal protocol: recording of participants talk when they have been asked to talk or think aloud

Interviews

case history: record of person’s important life events gathered and analysed in a case study

case study: in-depth study of one individual or group, usually qualitative in nature

clinical method: interview method using structure of questions to be asked but permitting tailorinng of later questions to the individuals responses

disguise: dimension of design which is the extent to which interviewees are kept ignorant of the aims of the questioning

focus group: group with common interest ho meet to discuss an issue in a collective interview in order for researchers to assess opinio

open-ended question: interview item to which interviewees can respond in any way they please and at any length

panel: stratified group who are consulted in order for opinion to be assessed

Questionnaires

Likert scale: scale on which respondant can choose from a dimension of responses, usually from strongly against/disagree to stonngly for/agree

semantic differential: scale measuring meaning of an object for the respondent by having them describe it using a point between the extremes of several bipolar adjectives

Thurstone Scale: scale in which raters assess the relative strength of each item and respondents agreeing with that item receive the average rated value for it

diagnostic item: item not obviously or directly connected to the attitude object, yet which correlates well with overall scores and therefor has discriminatory power

discriminatory power: extent to which items, or the test as a whole, separate people along the scoring dimension

factor analysis: statistical technique, using patterns of test or subtest correlations, which provides support for theoretical constructs by locating clusters

psychometric tests: yesys which attempt to quantify psychological variables, skills, abilities, character etc

reliability: consistency and stability of a test

chronbach’s alpha: a generalused Kuder-Richardson type test item discrimination/reliability for a response scale with several points

external reliability: stability of a test - its tendency to produce the same results when repeated

internal reliability: consistency of a test - extent to which items tend ti be measuring the same thing and not in opposition to one another

item analysis: checking each item in a scale by comparing its relationship with the total scores on the scale

split half: comparing scores on two parts (formed by a random and equal division of the items in a test)

response acquiescence: tendency for people to agree with test items as a habitual response

standardisation: adjusting test until scores on it form a normal distribution

validity: extent to which a test measures what was intended

concurrent validity: extent to which test results conform with those on some other measures taken at the same time

construct validity: extent to which test results support a network of research hypothesis based on the assumed characteristics of a theoretical psychological variable

content validity: extent to which test covers the whole relevant topic area

criterion validity: extent to which test scores can be used to make a specific prediction on another measure

face validity: extent to which the validity of a test is self-evident

known groups validity: test of criterion validity involving groups between whom scores on the test should differentiate

predictive validity: extent to which test scores can predict scores on another measure in the future

Comparison studies

cohort: large sample of people, often children, identified for longitudinal or cross-sectional study

cohort effect: confounding in cross-sectional study when two different age groups have had quite different experiences

cross-generational problem: confounding occurring when one longitudinally studied group is compared with another who have generally had quite different social experiences

cultural relativity: view that a person’s behaviour and characteristics can only be understood through that person’s own cultural environment

ethnocentrism: bias of viewing another’s culture from one’s own cultural perspective

indigenous psychology: psychological methodology developed by and within one culture, not imported from another

cross-cultural study: comparative study of two or more different societies or social subgroups

cross sectional study: comparative study of several groups captured for measurement at a single time point

cross-sectional, short-term longitudinal study: comparative study of several age groups followed through over a relatively short period

longitudinal study: comparative study of one group over a relatively long period

time-lag study: comparative study in which a sample of a specific age is selected each time the study is run (across relatively low intervals)

Measurement

categorical variable: variable is not measurable on a linear scale and which has only discrete values

frequency data: data presented as numbers of cases in specific categories

measured variable: variable is at least ordered

psychometrist: person who develops psychological measures and attempts to standardise the scales up to an interval level of measurement

qualitative difference: difference between cases in kind and not numerically measurable, though being different can be counted

quantitative difference: difference between cases measurable by number

continuous scale: scale on which it is always possible to subdivide units of measurement

discrete scale: scale containing only separated values of the variable measurement

interval level of measurement: level at which each unit measures an equal amount

nominal level of measurement: level at which numbers, if used, are mere labels identifying discrete categories of a categorical variable into which cases are sorted

ordinal level of measurement: level at which cases are arranged in rank positions

plastic interval level of measurement: scale which appears to be interval but on which equal numbers do not measure equal amounts

ratio level of measurement: level at which each unit measures an equal amount and proportions on the scale are meaningful; a real 0 exists.

Descriptive Statistics

absolute value: value of a number, ignoring its sign; a number treated as positive even if it is originally negative

average: common language term of central tendancy

bar chart: chart in which one axis represents a categorical or at least discrete variable

box plot: chart showing central spread of data and position of relative extremes

central tendency: formal term for any measure of the typical or middle value in a group

class interval: categories into which a continuous data scale is divided in order to summarise frequencies

deciles: interval of 10% on a continuous scale

deviation value/score: amount by which a particular score is different from the mean of its set

dispersion: technical term for any measure of the variation or spread of a sample of data or a population

bi-modal distribution: distribution with two prominent peaks

cumulative frequency distributions: distribution showing total numbers above or below each class interval

frequency: distribution showing how often certain values occurred

negative skew: distribution which is not symmetrical about the vertical centre and which contains a lot more lower than higher values, relative to the mode

positive skew: distribution which is not symmetrical about the vertical centre and which contains a lot more higher than lower values, relative to the mode

normal distribution: continuous distribution, bell-shaped, symmetrical about its mid-point and the result of a variable affected by many random influences

exploratory data analysis: close examination of data by a variety of means, including visual display, before submitting them to significance testing

frequency polygon: chart showing only the peaks of class intervals

histogram: chart containing whole of continuous data set divided into proportional intervals

mean: a measure of central tendency = mean of all absolute deviations

mean deviation: measure of dispersion = mean of all absolute deviations

median: mid-point of data set

medial position/location: place where median is to be found in the ordered data set

mode: most frequent value

parameter: statistical measure of population

percentile: point on continuous distribution which cuts off a certain percentage of cases

quartile: point on continuous distribution which cuts off one of the quarters

range: top minus bottom plus 1

sampling error: difference between sample mean and the true population mean

semi-interquartile range: distance between first and third quartile in a continuous distribution

standard deviation: the square root of the sum of all squared deviations, divided by N.

z-score/standard score: measure of individual deviation: number of standard deviations a particular score is from its sample mean

variance: square of standard deviation

variation ratio: proportion of non-modal values to all values

Probability and Significance

critical value: value with which a statistic, calculated from sample data, can be compared in order to decide whether a null hypothesis should be rejected; related to level of probability chosen.

directional hypothesis: prediciton which states inn which direction differences will occur

eyeball test: informal test of data made simply by inspection and mental calculation plus experience of values

non-directional hypothesis: prediction which does not state in which direction differences will occur

one-tailed test: test made if the research hypothesis is directional

two-tailed test: test made if the research hypothesis is non-directional

probability: a numerical measure of pure chance

empirical probability: a measure of probability based on existing data and comparing number of target events which have occurred with total number of relevant events

logical probability: a measure of probability calculated from analytical formulae and first principles

subjective probability: a measure of probability made on the basis of human internal, and often emotional, assessment

probability distribution: a histogram or table showing the probabilities associated with a complete range of possible events

significance levels: levels of probability at which it is agreed that the null hypothesis will be rejected

10% significance level: too high for rejection of the null but might merit further investigation

5% significance level: conventional significance level

1% significance level: preferred for greater confidence than the conventional one and which should be set where research is controversial or unique

Type 1 error: mistake made when rejecting the null hypothesis when it is true

Type 2 error: mistake made when retaining the null hypothesis when it is false

Simple Tests of Difference

degrees of freedom: number of cells in frequency table which are free to vary if row and column totals are known. also used in other tests where it defines the number of individual values free to vary when a group total is known

expected frequencies: frequencies theoretically expected in table if no relationship exists between variables

observed frequencies: frequencies actually obtained and submitted to a significance test using Chi-square

test statistic: the figure calculated at the end of a statistical test which is then compared with cirical value tables

chi-squared test: test of association between two variables, using unrelated data at a nominal level

goodness of fit test: frequency level test used to decide whether a given distribution is close enough to a theoretical pattern

binomial sign test: nominal level test of differences between two sets of related data

Mann-Whitney test: ordinal level test for differences between two sets of unrelated data using U

Wilcoxon rank sum: ordinal level test for differences between two sets of unrelated data using T

Wilcoxon signed ranks test: ordinal level test for differences between two related sets using T

ties: feature of data when scores are given identical rank values

homogeneity of variance: assumption to be satisfied by data before proceeding with a parametic test. occurs when the two variances are not significantly different

parametric test: relatively powerful significance test for data at interval level or above. the tests make estimations of population characteristics and the data tested must therefore satisfy certain assumptions

power of test: likelihood of a test detecting a significant difference when the null hypothesis is false

power efficiency: comparison of the power of two different tests of significance

related t-test: parametric difference test for related data

unrelated t-test: parametric difference test for unrelated data

robustness: tendency of test to give satisfactory probability estimates even when data assumptions for the test vary somewhat from the ideal

sampling distribution: hypothetical population distribution which can be estimated from sample statistics

standard error: standard deviation of a hypothetical sampling distribution

Correlation

correlation: relationship between two variables

coefficient correlation: numerical value of relationship between two variables

curvilinear correlation: relationship between two variables which gives a low value for r because the relationship does not fit a straight line but a good curve

negative correlation: relationship where as values of one variable increases, related values of the other tend to decrease

positive correlation: relationship where as values of one variable increases, related values of the other also increase

significance: measure of whether a correlation was likely to have occurred by chance or not

strength: measure of the degree of matching measured by a correlation

coefficient of determination: percentage of variability in one variable predictable from another using the correlation coefficient between them

guessing error: extent to which predictions of values of one variable are likely to be incorrect using values of another variable

multiple regression: technique in which the value of one variable is estimated using the correlationn with several other variables

pearson’s product-moment coefficient: parametric measure of correlation

phi co-efficient: measure of correlation between true dichotomous variables

point biserial correlation: measure of correlation where one variable is dichotomous

scattergram: diagram showing placement of paired values on a two-dimensional grid

spearmans rho: non-parametric ordinal level measure of correlation, correlation of ranks

variance estimate: estimate of variability in one variable using variance of a correlated variable

ANOVA

a prior comparisons: differences between means or combinations of means where were predicted from theory before the data were collected

analysis of variance (ANOVA): statistical technique which compares variances within and between samples in order to estimate the significance between sets of means

between groups sums of squares: sum of squares of deviations of group means from the grand mean; used to calculate the variance component related to the effect (distance between group means)

bonferroni t tests: procedure for testing several planned comparisons between groups of means

error rate per comparison: given the significance level set, the likelihood of an error in each tests made on the data

family wise error rate: the probability of having made at least one type error in all the tests made on one set of data

error sum of squares: sum of all the squares of deviations of each score from its group mean, for all scores in a set of data where there are two or more groups; used to calculate an estimate of the ‘unexplained variance‘ with which to compare the ‘explained variance of group means around the grand mean

F test/variance ratio test: comparison of two variances by dividing one by the other

grand mean: mean of all scores in a data set, irrespective of groups

linear coefficients: values to be entered into an equation for calculating linear contrasts

linear contrasts: procedure for testing beterrn individual pairs of means or combinations of means when planned comparisons have been made

mean sum of squares: sum of squares divided by degrees of freedom

Newman-Keuls test: procedure for testing all possible pairs of means in a data set for significance, so as long as number of groups is relatively low

pairwise comparisons: comparison of just two means from a set of means

planned comparisons: tests which was intended to make because of theoretical predictions, before data were collected

post hoc comparisons: tests between means, or groups of means, only decided upon after inspection of data

Tukey’s test of significance: procedure for testing all possible pairs of means from a data set where there are relatively large number of groups

unrelated design: an ANOVA design using only unrelated samples in all factors (independent variables)

factor in ANOVA: one of the IVs in a design with more than one IV

factorial design: a research design that involves more than one IV

interaction effect: effect of one factor which is significant but which depends upon only certain levels of other factors

levels in ANOVA: the different conditions of an IV

main effect: effect of one factor which is significant across all its levels taken together, irrespective of any other factors

mixed model: an ANOVA design using at least one repeated measure IV and at least one unrelated IV

simple effect: one level of a factor only has a significant effect across levels of the other factors

between subjects variation: variation associated with the differences between participants’ overall totals in repeat measures design

between conditions variation: variation calculated in a repeat measure design, which comes from how scores between conditions vary when the variation between participants overall totals have been removed

ANOVA residual: a term for the remaining variation in a repeat measures design when variation between subjects and between conditions has been removed

ANCOVA: statistical procedure used to investigate differences between two means which may be adjusted to allow for the fact that the two groups differ on a variable which correlates with the DV (covariate)

co-variate: a variable which correlates with the DV and on which two groups, who are being investigated for difference, differ. the biasing effect of the confounding variable can be adjusted for in ANCOVA.

criterion variable: variable which is being predicted in regression procedures

MANOVA: statistical procedure for testing the effects of one or more IVs on more than one DV

multiple regression: statistical procedure in which the correlations of several predictor variables with a criterion variable are summed to give a better prediction of that variable

multiple regression co-efficient: a value indicating the strength of prediction of the combined set of predictor variables being used in multiple regression

predictor variable: variable being used to predict a criterion variable in regression procedures

regression: procedure of predicting a criterion variable (Y) from a predictor variable (X) using the line of best fit around which correlated pairs of X and Y scores are arranged

regression coefficient: value indicating the extent to which each predictor variable predicts scores on the criterion variable in multiple regression procedures

regression residual: difference between an actual score and what it would be as predicted by a predictor variable using a regression procedure (Y-Y-hat)

suppressor variable: variable whose common variance can be partialled out of the variance of a predictor variable so that the latter can more accurately predict values of a criterion variable in multiple regression procedures

Analysing qualitative data

early analysis: formation of hypothesis and theoretical ideas during the acquisition of data

grounded theory: theory grounded in specific observational data = patterns emerge from the data set and are not imposed on it before it is gathered

negative case analysis: analysis of reasons why a single case does not fit patterns identified so far

triangulation: comparison of at least two views od the same thing

transcription: written recording of directly recorded speech, as exactly as possible, but depending upon approach; usually often includes pauses, intonation etc

Ethics

debriefing: informing participants about the full nature and rationale of the study they’ve experienced and removing any harm to self-image or self-esteem

deception: leading participant to believe that something other than the true IV is involved or, at least, not giving full information to the participant about the IV, DV or overall procedure

intervention: research which makes some alteration to people’s lives beyond the specific research setting, in some cases because there is an intention to remove disadvantage or make improvements of some kind in people’s overall condition

invasion of privacy: effect of research which intrudes on people’s personal lives

involuntary participation: taking part in research without agreement or knowledge of the study