Statistics Glossary

A

Alternative Hypothesis Inference

The hypothesis that states there is a statistically significant effect or relationship in the data. It is what researchers aim to support.

Symbol: H₁ or Ha

ANOVA (Analysis of Variance) Inference

A statistical method used to compare the means of three or more groups to see if at least one group mean is significantly different from the others.

Example: Comparing the average test scores of students from three different teaching methods.

Average Basic

A number expressing the central or typical value in a set of data. In statistics, this usually refers to the Mean.

Example: The average of 2, 4, and 6 is 4.

B

Bell Curve Distribution

A symmetrical probability distribution curve (Normal Distribution) shaped like a bell. Most data points cluster around the mean.

Bias Data Quality

A systematic error that results in an incorrect estimate of a population parameter, often caused by flawed sampling or measurement.

Bimodal Mode

A distribution or dataset that has two distinct modes (two values that appear most frequently).

C

Central Limit Theorem Distribution

A fundamental theory stating that the distribution of sample means will approach a normal distribution as the sample size increases, regardless of the population’s shape.

Correlation Relationship

A statistical measure that indicates the extent to which two or more variables fluctuate together.

Example: Height and weight typically have a positive correlation.

D

Data Set Basic

A collection of related sets of information that is composed of separate elements but can be manipulated as a unit by a computer.

Degrees of Freedom Inference

The number of values in a final calculation that are free to vary. Often calculated as n – 1.

Dependent Variable Relationship

The variable being tested and measured in an experiment. It “depends” on the independent variable.

Deviation Variability

The difference between a single data point and the mean of the data set.

I

Interquartile Range (IQR) Variability

The range between the first quartile (Q1) and the third quartile (Q3). It represents the middle 50% of the data.

Formula: IQR = Q3 – Q1

M

Mean Central Tendency

The arithmetic average of a dataset, calculated by adding all values together and dividing by the count of values. You can calculate this instantly using our Mean Calculator.

Formula: μ = (Σx) / n

Median Central Tendency

The middle value in a sorted list of numbers. If there is an even number of values, it is the average of the two middle numbers.

Mode Central Tendency

The value that appears most frequently in a data set.

N

Normal Distribution Distribution

Also known as the Gaussian distribution, it is a probability distribution that is symmetric about the mean.

Null Hypothesis Inference

A statement that there is no effect or no relationship between variables. It is the starting assumption in hypothesis testing.

Symbol: H₀

O

Outlier Data Analysis

A data point that differs significantly from other observations. It lies outside the overall pattern of distribution.

Example: In {2, 3, 2, 4, 105}, 105 is the outlier.

P

P-Value Inference

The probability that the observed results occurred by chance under the Null Hypothesis. A lower p-value indicates stronger evidence against H₀.

Note: Usually, a p-value < 0.05 is considered statistically significant.

Percentile Ranking

A measure used in statistics indicating the value below which a given percentage of observations in a group of observations falls. Calculate it quickly on our Percentile Calculator.

Example: The 20th percentile is the value below which 20% of the observations may be found.

Poisson Distribution Distribution

A discrete probability distribution that expresses the probability of a given number of events occurring in a fixed interval of time or space.

Population Scope

The entire pool from which a statistical sample is drawn. It represents 100% of the group of interest.

R

Range Variability

The difference between the lowest and highest values in a set of data.

Formula: Range = Max – Min

Regression Analysis Relationship

A set of statistical processes for estimating the relationships between a dependent variable and one or more independent variables.

S

Sample Scope

A subset of individuals from a larger population. Statistics are often calculated on samples to estimate population parameters.

Significance Level (Alpha) Inference

The threshold used to determine whether a p-value is small enough to reject the null hypothesis. Common levels are 0.05 or 0.01.

Symbol: α

Skewness Distribution

A measure of the asymmetry of the probability distribution of a real-valued random variable.

Types: Positive (right-skewed) or Negative (left-skewed).

Standard Deviation Crucial

A measure of the amount of variation or dispersion of a set of values. A low standard deviation indicates that the values tend to be close to the mean. Solve it instantly using our Standard Deviation Calculator.

Symbol: σ (sigma) for population, s for sample.

T

Type I Error Error

A “false positive” error that occurs when the null hypothesis is rejected even though it is true.

Type II Error Error

A “false negative” error that occurs when the null hypothesis is NOT rejected even though it is false.

V

Variance Variability

The expectation of the squared deviation of a random variable from its mean. It measures how far a set of numbers is spread out.

Relation: Variance is the Standard Deviation squared (σ²).

Z

Z-Score Standardization

A statistical measurement that describes a value’s relationship to the mean of a group of values. It is measured in terms of standard deviations from the mean. Refer to our Z-Score Table for values.

Formula: z = (x – μ) / σ