Statistics

Categorical variable Measurement that classes people, object or places into groups. There are two types: nominal and ordinal

Continuous variable Numerical measurement. There are two types: interval and ratio

Dependent variable Phenomenon being studied, outcomes

Descriptive research A study to describe a particular phenomenon as it occurs in a sample

Empirical Something measurable, observable and tangible

Empirical relationship Causal requirement that the independent and dependent variables have an observed relationship with one another

Exploratory research The study of issues that have seldom been examined by prior research and may be lacking in firm theory

Evaluation research The study of results or programmes or interventions to determine their effectiveness

Hypothesis A single proposition, deduced from a theory, that must hold true for a theory to be considered valid

Independent variable Factor or characteristic being used to attempt an explanation or prediction of a dependent variable

Nominal variable Classes people, objects or places into different groups according to a characteristic that cannot be ranked (i.e. self-defined ethnicity, sex)

Nonspurious Causal requirement that the relationship between an independent variable and dependent variable are not the result of a third variable omitted from the analysis

Ordinal variable Classes people, objects or places into group according to characteristics that can be ranked in terms of quantity (i.e. income brackets)

Population People, objects or places under study

Sample A subset taken from a population using people, objects or place, used as a way to generalise the population

Temporal order Causal requirement that an independent variable must precede a dependent variable (direction of relationship)

Theory Proposed explanations about reality that are bound by logic and evidence

Unit of analysis The object or target of study - individuals, crime incidents, micro-meso-macro geographical units

Bivariate Analysis composed of two variables, often one is designated an independent variable and the other a dependent variable

Classes Categories or groups within nominal or ordinal variables

Contingency table Shows overlap between two variables

Cumulative Frequency, proportion or percentage derived from adding a unit to all those below it

Deviation score Distance between mean of a data set and any given raw value

Dispersion Spread of variability among the values in a distribution

Frequency Number of times a particular unit is counted in a data set

Longitudinal variable Variables measured repeatedly over time

Mean Arithmetic average of a set of data

Measures of central tendency Denote where the values in a data set cluster, i.e., the mode, median and mean

Median The value that cuts a distribution in half 50/50

Mode Most frequently occurring category or value

Negative skew A set of values that cluster to the right

Normal distribution A set of values that cluster in the centre and tail off to the left (negative) and right (positive), a bell curve

Percentage Standardisation of a frequency ranging from 0.00 to 100.00

Positive skew A set of values that cluster to the left

Proportion Standardisation of a frequency ranging from 0.00 to 1.00

Standard deviation Measure of dispersion that is the mean of the deviation scores

Trend Patterns indicating a direction of travel, increasing, decreasing or remaining stable over time

Univariate Involving one variable

Binomial Trial with two possible outcomes

Empirical outcome Numerical result from a sample, also known as observed outcome

Probability distribution Table or graph showing entire set of probabilities associated with every possible empirical or observed outcome

Probability Likelihood an event will occur, representing a prediction

Theoretical prediction Prediction grounded in logic