DataTerminology.comNEW
A proposed explanation or claim about a phenomenon that can be tested using data and statistical methods.
DESCRIPTION
A hypothesis articulates a testable statement about relationships, effects, or mechanisms. In statistics, hypotheses are formalized and evaluated via tests, confidence intervals, or Bayesian updating. Clear hypotheses guide experimental design, data collection, and analysis plans. Good hypotheses are specific, measurable, and falsifiable. Distinguish hypotheses from theories, which are broader explanatory frameworks supported by evidence.
ALTERNATIVE DEFINITIONS
Wikipedia
A hypothesis is a proposed explanation for a phenomenon.
Concise emphasis on explanation and propositional nature.
Encyclopædia Britannica
Hypothesis, something supposed or taken for granted, for the sake of argument; a suggestion or proposition made as a basis for reasoning.
Highlights provisional and reasoning-based character.
RELATED TERMS
Null Hypothesis Alternative Hypothesis Inference Assumptions Research Question Evidence Falsifiability Bayesian Priors Model
COMPETING TERMS
Theory
RELATIONS
KNOWLEDGE AREAS
Mathematics Data Science Testing & Validation
TARGET AUDIENCE
Data Scientist Data Analyst Information Analyst
EXTERNAL SOURCES
- Wikipedia - Hypothesis
- Stanford Encyclopedia of Philosophy - Context on hypotheses in science
- NIST/SEMATECH - Foundations of statistical reasoning
TOP QUESTIONS
What makes a good Hypothesis in data science?
Specific, measurable, and falsifiable statements that align with business goals and can be tested with available data.
Category: Best Practice
How does a Hypothesis differ from a theory?
A hypothesis is a specific testable claim; a theory is a broader explanatory framework supported by substantial evidence.
Category: Misunderstanding
Do I always need a Hypothesis before analysis?
Exploratory analysis can generate hypotheses, but confirmatory analysis should test pre-specified hypotheses to avoid p-hacking.
Category: Opinion
How many Hypotheses should I test?
Limit to a manageable set tied to decisions, and adjust for multiple comparisons to control false positives.
Category: Requirements
What is a directional versus non-directional Hypothesis?
Directional predicts an increase or decrease; non-directional predicts a difference without specifying direction.
Category: Concept
How do I ensure my Hypothesis is testable?
Define measurable variables, a clear effect size, and a method of analysis before collecting data.
Category: Best Practice
What is the risk of vague Hypotheses?
They lead to ambiguous analyses and uninterpretable results. Precision improves interpretability and replicability.
Category: Risk
Can Bayesian methods test a Hypothesis?
Yes, via Bayes factors or posterior probability statements about parameters and models.
Category: Technique
How do Hypotheses guide experimental design?
They determine variables, controls, sample size, and analysis plans, ensuring statistical power and relevance.
Category: Usage