Glossary
Statistical terms simply explained.
A
- Alternative Hypothesis
- The hypothesis accepted when the null hypothesis is rejected. It posits an effect or difference (H₁ or Hₐ).
- ANOVA
- Analysis of Variance. A method for comparing the means of three or more groups.
C
- Chi-Square Test
- A non-parametric test for analyzing categorical data. Tests associations or goodness of fit with an expected distribution.
- Confidence Interval
- A range of values that contains the true population parameter with a specified probability (e.g., 95%).
- Correlation
- A statistical measure of the linear relationship between two variables. Values range from -1 to +1.
D
- Degrees of Freedom
- The number of values in a calculation that are free to vary (df). Influences the shape of the test distribution.
E
- Effect Size
- A measure of the practical significance of a statistical result, independent of sample size. Examples: Cohen's d, η², r.
H
- Homogeneity of Variance
- The assumption that variances in different groups are equal. Also known as homoscedasticity.
L
- Levene's Test
- A test for homogeneity of variance (equal variances) between groups. A prerequisite for many parametric tests.
M
- Mean
- The arithmetic average of all values. Calculated as the sum of all values divided by the number of observations.
- Median
- The middle value of an ordered data set. More robust to outliers than the mean.
N
- Normal Distribution
- A symmetric, bell-shaped probability distribution. Many statistical tests assume normally distributed data.
- Null Hypothesis
- The hypothesis that there is no effect or no difference (H₀). It is tested and either retained or rejected.
O
- Outlier
- A data point that deviates markedly from the rest of the data. Can distort statistical results.
P
- p-Value
- The probability of obtaining the observed (or a more extreme) result if the null hypothesis is true. Common significance level: p < 0.05.
R
- Regression
- A method for modeling the relationship between a dependent variable and one or more independent variables.
S
- Sample
- A subset of the population selected for statistical analysis.
- Shapiro-Wilk Test
- A statistical test to check whether a sample comes from a normally distributed population.
- Significance Level
- The probability (α) of incorrectly rejecting the null hypothesis. Common: α = 0.05 (5%).
- Standard Deviation
- A measure of the spread of data around the mean. The square root of the variance.
- Statistical Power
- The probability (1 - β) of detecting an effect that actually exists. Also referred to as power.
T
- t-Test
- A parametric test for comparing the means of two groups. Variants: independent, paired, one-sample.
- Type I Error
- Incorrectly rejecting a true null hypothesis (false positive). The probability is controlled by α.
- Type II Error
- Incorrectly retaining a false null hypothesis (false negative). The probability is denoted as β.
V
- Variance
- A measure of data spread. Calculated as the mean squared deviation from the mean.