CSS 214: Applied Statistics in Criminology and Security Studies Review

Comprehensive vocabulary flashcards covering basic statistical concepts, variable types, measurement scales, sampling techniques, and statistical tests applied in Criminology and Security Studies.

Statistics

The science of collecting, organizing, presenting, analyzing, and interpreting data for decision-making.

Population

The entire group of individuals or items under study, such as all inmates in Nigerian prisons.

Sample

A subset of the population selected for study, such as 500 inmates selected from prisons for research.

Census

The complete enumeration of the entire population.

Parameter

A numerical value describing a population.

Statistic

A numerical value describing a sample.

Variable

A characteristic that can change or take different values, such as the age of an offender or type of crime.

Independent Variable

The variable that causes change; for example, in the relationship Poverty $\rightarrow$ Crime, poverty is this variable.

Dependent Variable

The variable that is affected or explained; for example, the crime rate.

Intervening Variable

A variable that explains the relationship between the independent and dependent variables, such as unemployment in the path: Poverty $\rightarrow$ Unemployment $\rightarrow$ Crime.

Moderating Variable

A variable that changes the strength or direction of a relationship, such as urban vs. rural settings affecting the link between poverty and crime.

Control Variable

A variable kept constant during analysis to avoid distortion, like age or gender.

Extraneous Variable

A variable that affects the outcome but is not part of the study, such as media influence on crime perception.

Confounding Variable

A variable that mixes up the effect of the independent variable, making results unclear.

Qualitative Data

Categorical data that describes qualities rather than numbers, such as gender or type of crime.

Quantitative Data

Numerical data, which can be subdivided into discrete and continuous types.

Discrete Data

Countable numerical values that cannot be broken into fractions, such as the number of criminals arrested.

Continuous Data

Measurable values that can take decimals, such as age ($21.5\text{ years}$) or time.

Primary Data

Data collected directly by the researcher through interviews, questionnaires, or observation.

Secondary Data

Data already collected by others, including police records, court records, and government reports.

Nominal Scale

A level of measurement where data are classified into categories without order or ranking, such as crime type or religion.

Ordinal Scale

A scale where data are ranked or ordered, but the differences between ranks are not measurable, such as crime severity levels.

Interval Scale

Numeric data with equal intervals but no true zero, such as IQ scores or temperature.

Ratio Scale

Data with equal intervals and a true zero point, such as number of crimes, age, or income level.

Probability

The likelihood or chance that an event will occur, expressed between $0$ and $1$.

Simple Random Sampling

A probability sampling method where every member of the population has an equal chance of selection.

Systematic Sampling

A sampling method where selection is done at regular intervals, such as choosing every $n^{th}$ item.

Stratified Sampling

A method where the population is divided into sub-groups (strata) and samples are taken from each.

Cluster Sampling

A method where the population is divided into groups, and entire clusters are selected randomly.

Snowball Sampling

A non-probability sampling method where one respondent refers others, such as an ex-offender referring other former criminals.

Bar Chart

A visual representation for categorical data where bars are separated and height shows frequency.

Histogram

A graph for continuous data grouped in intervals where bars touch each other to show distribution.

Ogive

A cumulative frequency curve used for finding the median and percentiles.

Mean

The arithmetic average calculated as \text{Mean} = \frac{\text{\textSigma} X}{N}.

Median

The middle value when data is arranged in order.

Mode

The most frequently occurring value in a dataset.

Standard Deviation

The square root of variance, showing how data is spread around the mean in original units.

Normal Distribution

A bell-shaped, symmetrical distribution where $\text{Mean} = \text{Median} = \text{Mode}$.

Z-Score

A standardized score indicating how far a value is from the mean in standard deviation units, calculated as z = \frac{x - \text{\textmu}}{\text{\textsigma}}.

Null Hypothesis ($H_0$)

A statement assuming there is no significant relationship or difference between variables.

Alternative Hypothesis ($H_1$)

A statement assuming a significant relationship or difference exists.

Level of Significance (\text{\textalpha})

The probability of rejecting a true null hypothesis, commonly set at $0.05$ or $0.01$.

Type I Error

Rejecting a true null hypothesis, also known as a false positive.

Type II Error

Failing to reject a false null hypothesis, also known as a false negative.

Correlation

A statistical method used to measure the strength and direction of the relationship between two variables, ranging from $-1$ to $+1$.

Pearson Correlation

A correlation coefficient used specifically for continuous numerical data.

Regression Analysis

A method used to examine relationships and predict the value of a dependent variable based on independent variables.

R-Square ($R^2$)

A value showing how much of the variation in the dependent variable is explained by the predictors.

Chi-Square (\text{\textchi}^2) Test

A non-parametric test used to determine if there is a significant association between two categorical variables using the formula \text{\textchi}^2 = \text{\textSigma} \frac{(O - E)^2}{E}.

T-Test

A statistical test used to compare the means of two groups to check for significant differences.

ANOVA

Analysis of Variance; a technique used to determine significant differences among the means of three or more groups.

SPSS

Statistical Package for the Social Sciences; software used for data entry, analysis, and interpretation of results.

Recidivism

The tendency of a criminal to re-offend after punishment or release from prison.

Data View

The screen in SPSS used for entering raw data, where rows represent cases and columns represent variables.

Variable View

The screen in SPSS used to define the characteristics of variables, including name, type, and measurement level.