Glossary

Plain-language definitions of terms used in this guide and in StatPrism’s output.

p-value

The probability of seeing a result at least as extreme as the one observed if there were really no effect. Small values (commonly < .05) are taken as evidence against “no effect”.

Confidence interval (CI)

A range that, under repeated sampling, would contain the true value a stated percentage of the time (StatPrism reports 95% CIs). Wider intervals mean more uncertainty.

Effect size

How big an effect is, independent of sample size — e.g. Cohen’s d (mean differences), r (correlation), η²/η²p (ANOVA), Cramér’s V (contingency). Significance says whether an effect exists; effect size says whether it matters.

Degrees of freedom (df)

A count tied to sample and model size that calibrates a test’s reference distribution.

Numeric / Nominal / Ordinal

Column types. Numeric = quantities; Nominal = unordered categories; Ordinal = ordered categories. See Importing data.

Missing data

Cells with no answer. In numeric columns these stay genuinely missing; in text columns a blank is read as the literal nan. Handle with Impute Missing or Filter.

Parametric vs non-parametric

Parametric tests (t-test, ANOVA, Pearson) assume things like normality; non-parametric tests (Mann–Whitney, Kruskal–Wallis, Wilcoxon, Friedman, Spearman) make fewer assumptions and use ranks.

Normality

Whether a variable approximately follows a bell-shaped (normal) distribution — an assumption of several parametric tests. Checked with Shapiro–Wilk, Kolmogorov–Smirnov, or Anderson–Darling.

Homogeneity of variance

Whether groups have similar spread — an assumption of the standard t-test/ANOVA. Welch’s versions relax it.

Correlation

The strength and direction of association between two variables, from −1 to +1. Pearson measures linear association; Spearman/Kendall measure rank (monotonic) association.

Partial correlation

The association between two variables after removing the influence of one or more control variables.

Reliability (Cronbach’s α / McDonald’s ω)

How consistently a set of items measures the same thing. Higher is better; very low values suggest the items don’t form a coherent scale. See Reliability.

Factor / loading

In factor analysis, a factor is an underlying dimension; a loading is how strongly an item reflects a factor. See Exploratory factor analysis and Confirmatory factor analysis.

Statistical power

The chance a study will detect an effect that is really there. Power analysis relates power, sample size, effect size, and significance level. See Power analysis.

Standardised coefficient (β)

A regression coefficient expressed in standard-deviation units, so predictors on different scales can be compared.

One-hot / indicator column

A 0/1 column marking whether a category applies. Created by One-hot encoding (from a single-select column) or Split Multi-Select (from a checkbox question).

APA style

The American Psychological Association’s formatting conventions for tables and statistics, widely used in the social sciences. StatPrism formats output to match.