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Statista Glossary
Definitions relating to statistics
A
Autocorrelation
Attribute
Artificial intelligence (AI)
Arithmetic mean
Approximation
Alternative hypothesis
Algorithm
Aggregated data
Acquiescence bias
Absolute frequency
B
Bootstrap/bootstrapping
Blind study - double-blind study
Bivariate data
Binomial distribution
Bias
C
Cross-sectional data
Correlation
Confidence level
Conditional probability
Coefficient of correlation
Cluster sample
Cluster analysis
Central limit theorem
Causality
Categorical
D
Distribution function
Distribution
Dispersion parameter
Dispersion
Descriptive statistics
Diagrams
Dependent variable
Dependence
Density function
Demographics
Deduction
E
Extreme value
Extrapolation
Experiment
Exogenous variable
Excess
Endogenous variable
Empirical probability
Elementary event
Ecological fallacy
F
Full population survey
F-test
Frequency distribution
Forecast
False positive
False negative
G
Growth rate
Gini coefficient
Generalized least square (GLS) model
H
Hypothesis
Hyperparameter
Histogram
Hallucination
I
Interval scale
Interpolation
Induction
Individual data
Indicator
Independent variable
J
Joint probability
K
Kurtosis
K-means
L
Longitudinal study
Linear model
Linear exponential smoothing
Likert scale
Level of measurement
Leading question
Law of large numbers
M
Mode
Mid-range
Metric scale
Median
Matrix
Margin of error
Machine learning (ML)
N
Numerical
Null hypothesis
Normal distribution
Nominal scale
Noise
O
Overfitting
Outlier
Ordinal scale
Opinion poll
Observation
Objectivity
P
P value
Probability
Predictive model
Population
Panel data
Q
Quota sampling
Quartile
Quantitative data
Quantile
Qualitative data
R
Root mean squared error
Representativeness
Reliability
Relative frequency
Regression analysis
Raw data
Rating scale
Range
Random sample
Random forest
S
Survey
Supervised learning
Subjective and objective propability
Statistical unit
Statistical significance
Statistical hypothesis testing
Standard deviation
Spurious correlation
Social desirability bias
Skewness
Simple moving average
Selection method
Secondary data
Sample survey
Sample
T
t-test
Training dataset
Trend
Time series analysis
Time series
Test dataset
U
Unsupervised learning
V
Vector
Variance
Variable
Validity
Validation dataset
W
Weighted regression
Weighted average
X
x-variable
Y
y-variable
Z
z-test