Is a hypothesis a guess?

No, a hypothesis is an educated, testable prediction based on prior knowledge and observations, not a random guess, because it must be falsifiable through experimentation.

Which is better to have, a theory or a hypothesis?

Neither is inherently better, because a hypothesis serves as a starting point for investigation, while a theory represents a mature, validated explanation that has survived rigorous testing.

Does it cost more to test a hypothesis than to develop a theory?

Testing a hypothesis typically costs less per experiment, whereas developing a theory requires cumulative funding for many studies, so the total investment for a theory is usually higher.

What are the risks of treating a hypothesis as a theory?

The main risk is drawing premature conclusions, because an untested hypothesis lacks the evidence needed to guide decisions, which can lead to incorrect assumptions and wasted resources.

Can a hypothesis be compatible with an existing theory?

Yes, a hypothesis is often compatible with an existing theory when it makes a specific, testable prediction that fits within the broader theoretical framework.

What is a common beginner mistake when using the terms theory and hypothesis?

A common mistake is using them interchangeably in everyday speech, because this blurs the critical distinction between an unverified prediction and a well-established explanation.

Can the terms theory and hypothesis be used interchangeably in science?

No, they cannot be used interchangeably in science, because a hypothesis is a tentative proposal for testing, whereas a theory is a comprehensive explanation with strong supporting evidence.

What is a real-world use case for a hypothesis in a scientific field?

In medicine, a researcher uses a hypothesis to predict that a new drug reduces blood pressure, then designs a clinical trial to test that specific prediction before any theory is formed.

Can I switch from calling my idea a hypothesis to a theory?

Yes, you can switch only after your hypothesis has survived repeated testing and accumulated sufficient evidence to become a widely accepted explanation, not simply because you prefer the term.

Difference Between

Difference Between Theory and Hypothesis

Written byNex Virox Team

Editorial Team

Reviewed byVarshal Nirbhavane

Senior SEO & Organic Growth Professional · 5+ years

Published: August 27, 202619 min read

Quick answer

The main difference between Theory and Hypothesis is that a theory is a well-tested, widely accepted explanation supported by extensive evidence, while a hypothesis is a testable, tentative prediction awaiting verification. Theory is a comprehensive, validated framework, while Hypothesis is an initial, falsifiable guess.

Key takeaways

Core distinction: A hypothesis is a testable prediction, while a theory is a well-substantiated explanation.
How each works: Hypotheses guide single experiments; theories integrate many confirmed hypotheses into broader frameworks.
Effort and evidence: Hypotheses require limited data to propose; theories demand extensive, repeated, and validated evidence.
Best-fit use case: Use hypotheses for new research questions; use theories for explaining established natural phenomena.
Common decision mistake: People wrongly call an untested guess a theory, when it remains only a hypothesis.

Table of Contents18 sections

Difference Between Theory and Hypothesis: Comparison Table

Aspect	Theory	Hypothesis
Definition	Broad, well-substantiated explanation integrating many confirmed observations and tested hypotheses.	Specific, testable prediction about the expected relationship between two or more variables.
Purpose	Explains why a natural phenomenon occurs by unifying multiple established facts and laws.	Proposes a tentative answer to guide data collection and experimental design.
Core Mechanism	Synthesizes verified evidence into a coherent framework that makes sense of diverse observations.	Operationalizes variables into measurable terms so a single experiment can confirm or refute it.
Scope	Broad and comprehensive, covering many related phenomena across different contexts and time periods.	Narrow and focused, addressing a single question or a limited set of variables.
Maturity	Mature and stable, having survived decades or centuries of repeated testing and peer review.	Early-stage and provisional, typically formulated at the start of a research project.
Evidence Level	Backed by a large body of convergent evidence from many independent lines of inquiry.	Supported by limited or preliminary data, often from a single study or observation.
Testability	Generates multiple testable predictions that researchers can verify through diverse experiments.	Designed for direct testing through a single experiment, survey, or observational study.
Falsifiability	Can be revised or replaced if new contradictory evidence emerges from rigorous testing.	Must be structured so that a negative result clearly demonstrates the prediction is wrong.
Confirmation Status	Extensively confirmed through independent replication across many research groups and methods.	Unconfirmed until tested; remains a proposal until data support or reject it.
Predictive Power	Makes broad predictions about future observations and previously unexplained phenomena.	Makes a narrow prediction about the specific outcome of one planned investigation.
Explanatory Depth	Provides deep causal explanations that connect multiple laws, facts, and mechanisms.	Offers a shallow, surface-level guess about a single relationship between variables.
Complexity	Complex structure involving multiple sub-concepts, laws, and interconnected mechanisms.	Simple statement usually expressible in one sentence with two variables.
Formulation Time	Developed over years or decades through cumulative research by many scientists.	Formulated quickly, often in minutes or hours, before beginning data collection.
Revision Frequency	Revised rarely, only when major new evidence requires adjusting the framework.	Revised frequently, often after each failed experiment or new preliminary finding.
Research Role	Serves as the foundational framework guiding entire fields of ongoing investigation.	Serves as the starting point for a single study or short research project.
Data Requirement	Requires massive datasets accumulated from thousands of studies over long periods.	Requires only the data from one experiment or observation to be evaluated.
Certainty Level	High confidence among experts, though never considered absolute or final truth.	Low confidence until tested; explicitly uncertain and open to disproof.
Scientific Status	Accepted as the current best explanation by the relevant scientific community.	Not yet accepted; only a candidate explanation awaiting empirical verification.
Application	Applied to solve real-world problems in medicine, engineering, and technology development.	Applied only within the research setting to structure the specific investigation.
Development Cost	Requires substantial funding across many grants, institutions, and research programs.	Requires minimal funding, often just the resources for one small experiment.
Development Time	Takes years to decades of cumulative work by hundreds of researchers worldwide.	Takes days or weeks to develop and write up before testing begins.
Peer Review	Undergoes continuous scrutiny through publication, replication, and scientific debate.	May be reviewed informally by advisors or colleagues before the experiment runs.
Failure Impact	Failed predictions can trigger major paradigm shifts and reshape entire research fields.	Failed predictions simply eliminate one option and refine the next hypothesis.
Common Misuse	Colloquially misused to mean a guess, despite representing the strongest form of science.	Colloquially treated as proven fact, despite being the weakest and most tentative form.
Everyday Example	Germ theory explains how microorganisms cause infectious disease across all transmission routes.	Hypothesis that handwashing reduces infection rates in a specific hospital ward.
Typical Users	Used by established scientists, researchers, and professionals applying established knowledge.	Used by students, early-career researchers, and scientists designing new experiments.
Educational Role	Taught as established curriculum content in advanced courses and textbooks.	Taught as the core skill in scientific method exercises and research design classes.
Publication Format	Published in review articles, textbooks, and comprehensive scientific syntheses.	Published in the introduction or methods section of a single research paper.
Limitation	Cannot be proven absolutely; always remains open to future revision or replacement.	Cannot explain phenomena broadly; only addresses the narrow tested relationship.
Best-Fit Scenario	Choose a theory when you need a reliable framework to explain or predict real-world outcomes.	Choose a hypothesis when you need a testable prediction to start a new investigation.

What Is Theory?

Theory is a well-tested explanation of a natural phenomenon, built from repeated observation and experimentation. It organizes facts into a coherent framework that predicts future outcomes. A theory exists to explain why things happen, not merely to describe what happens.

Definition of Theory

A theory is a systematically organized set of principles, supported by substantial evidence, that explains a broad class of phenomena and generates testable predictions. It integrates multiple confirmed hypotheses into a unified model. Scientific theories are provisional, subject to revision when new evidence contradicts them.

Key Characteristics of Theory

Characteristic	What It Means in Practice
Evidence-backed	Built on thousands of reproducible observations from independent research groups worldwide.
Predictive power	Forecasts future observations or experimental results before they are measured.
Explanatory scope	Accounts for a wide range of related phenomena under one unifying framework.
Testable	Generates specific hypotheses that researchers can confirm or falsify through experiments.
Falsifiable	Makes claims specific enough that contrary evidence could logically disprove it.
Provisional	Open to modification or replacement when new, conflicting data emerges.
Parsimonious	Prefers the simplest explanation that adequately fits all known observations.
Consistent	Does not contradict other established theories or confirmed laws of nature.
Unifying	Connects previously separate facts and hypotheses into a single coherent model.
Peer-reviewed	Has survived scrutiny and replication by independent experts in the field.

Common Examples of Theory

Evolution by Natural Selection – explains species diversity through heritable trait variation and differential survival.
Germ Theory of Disease – establishes that specific microorganisms cause specific infectious illnesses.
Plate Tectonics – explains continental drift, earthquakes, and mountain building via lithospheric movement.
Atomic Theory – posits that all matter consists of discrete, indivisible particles called atoms.
Quantum Mechanics – describes particle behavior at atomic scales using probability and wave functions.
General Relativity – explains gravity as the curvature of spacetime caused by massive objects.
Cell Theory – states that all living organisms are composed of one or more cells.
Heliocentric Theory – places the Sun, not Earth, at the center of the solar system.
Big Bang Theory – describes the universe's origin from an extremely hot, dense state.
Kinetic Molecular Theory – explains gas behavior through the constant motion of particles.

Advantages and Limitations of Theory

Advantages	Limitations
Provides a reliable framework for interpreting new experimental data and observations.	Can become entrenched, causing researchers to resist valid evidence that contradicts it.
Enables accurate predictions that drive technological innovation and practical applications.	Cannot prove absolute truth; future evidence may always overturn a current theory.
Unifies disparate findings, reducing scientific knowledge to coherent, teachable principles.	Often oversimplifies complex reality, ignoring edge cases and exceptions to the rule.
Guides resource allocation by directing researchers toward the most promising questions.	Requires specialized expertise to understand, creating barriers for non-specialists.
Offers testable predictions that allow continuous self-correction within the scientific method.	May be misapplied beyond its intended scope, leading to invalid conclusions.
Stimulates new hypotheses and experiments that expand the boundaries of knowledge.	Can be slow to change, with outdated models persisting for decades after disproof.
Provides a shared language and conceptual base for collaboration across disciplines.	May carry cultural or historical baggage that biases interpretation of new data.
Helps distinguish genuine scientific claims from unsupported pseudoscientific assertions.	Mathematical or conceptual complexity can make theories inaccessible to public scrutiny.
Facilitates engineering and medicine by providing reliable cause-and-effect relationships.	Often relies on unobservable entities, making direct verification impossible.
Accumulates explanatory power over time as refinements incorporate new discoveries.	Frequent revisions can undermine public confidence in scientific consensus.

What Is Hypothesis?

Hypothesis is a testable, falsifiable prediction about the relationship between two or more variables. It gives scientific research a clear direction by stating a specific expected outcome. A hypothesis exists to be empirically tested and either supported or rejected through systematic observation and experimentation.

Definition of Hypothesis

A hypothesis is a precise, provisional statement that proposes a measurable relationship between variables and is formulated so it can be empirically tested through observation or experimentation. It must be falsifiable, meaning evidence can potentially disprove it, and it serves as the foundational prediction guiding scientific inquiry.

Key Characteristics of Hypothesis

Characteristic	What It Means in Practice
Testable	Variables must be measurable so researchers can collect data to confirm or reject the prediction.
Falsifiable	There must be a possible observation or experiment that could prove the statement false.
Specific	It names exact variables and the predicted direction of their relationship, avoiding vague generalities.
Empirical	It relies on observable evidence gathered through the senses or instruments, not on intuition or belief.
Provisional	It is a temporary explanation that remains open to revision or replacement as new data emerges.
Precise	It uses clear operational definitions so other researchers can replicate the exact same test procedure.
Logical	It follows deductively from existing theory or prior observations, making it a rational next step.
Parsimonious	It offers the simplest plausible explanation that accounts for observed facts without unnecessary complexity.
Directional	It often predicts whether the relationship is positive, negative, or neutral between the named variables.
Objective	It is framed without personal bias, value judgments, or emotional language that could skew the test.

Common Examples of Hypothesis

Plant growth – Increasing sunlight exposure from 4 to 8 hours daily will increase bean plant height over 30 days.
Sleep and memory – Adults who sleep 8 hours nightly will recall 20% more word pairs than adults sleeping 5 hours.
Smoking and lung capacity – Long-term smokers show significantly reduced forced expiratory volume compared to non-smokers.
Temperature and reaction time – Higher ambient temperatures above 30°C will slow human reaction times in cognitive tests.
Fertilizer and yield – Adding nitrogen-based fertilizer at 50 kg per hectare will increase wheat yield by 15%.
Music and focus – Listening to instrumental classical music during study sessions improves test scores versus silence.
Exercise and mood – Thirty minutes of moderate aerobic exercise will reduce self-reported anxiety scores immediately afterward.
Social media and attention – Limiting daily social media use to 30 minutes will improve sustained attention on continuous tasks.
Diet and cholesterol – Replacing saturated fats with olive oil will lower LDL cholesterol levels within eight weeks.
Water and germination – Seeds soaked in warm water for 12 hours will germinate faster than dry-planted seeds.

Advantages and Limitations of Hypothesis

Advantages	Limitations
Focuses research on a specific measurable outcome, saving time and resources compared to open-ended exploration.	Confirmation bias can creep in, where researchers unconsciously favor data that supports their initial prediction.
Provides a clear benchmark for statistical testing, allowing objective decisions about whether results are significant.	A poorly constructed hypothesis with vague variables produces ambiguous results that cannot be meaningfully interpreted.
Enables replication by other scientists because the hypothesis specifies exact variables, conditions, and measurements.	It can narrow thinking too early, causing researchers to overlook unexpected phenomena that a broader question might reveal.
Forces operational definitions, turning abstract concepts like anxiety or intelligence into concrete measurable quantities.	Many real-world phenomena involve multiple interacting variables that a single simple hypothesis cannot capture.
Builds cumulative scientific knowledge because each supported hypothesis strengthens the theoretical framework behind it.	Supporting a hypothesis never proves it true; it only shows the evidence is consistent, leaving room for alternative explanations.
Guides data collection decisions, including sample size, measurement tools, and statistical analysis methods.	Falsification can be difficult in practice when measurement error, confounding variables, or small effect sizes obscure true patterns.
Communicates research intent clearly to funders, reviewers, and the public, making the study's purpose transparent.	Researchers may engage in p-hacking, tweaking analyses until results cross significance thresholds, undermining the hypothesis test.
Allows comparison across studies because standard hypothesis formats make different experiments directly comparable.	It assumes the researcher has enough prior knowledge to form a meaningful prediction, which is impossible in truly novel domains.
Facilitates ethical review because the specific prediction helps committees assess risks and benefits of the proposed procedures.	Publication bias means null results from failed hypotheses often go unpublished, distorting the evidence base.
Encourages rigorous methodology by demanding control groups, randomization, and blinding to isolate the variable of interest.	An overly complex hypothesis with many variables becomes untestable because isolating each factor's effect is practically impossible.

Similarities Between Theory and Hypothesis

Shared Aspect	How Theory and Hypothesis Are Alike
Scientific foundation	Both a theory and a hypothesis are core components of the scientific method used to explain natural phenomena.
Testable propositions	A theory and a hypothesis both propose ideas that scientists can test through observation, experimentation, or further data collection.
Evidence-driven nature	Both a theory and a hypothesis rely on empirical evidence to either support, refine, or reject their core claims.
Initial observations	A hypothesis and a theory both originate from careful observations of patterns, events, or relationships in the natural world.
Falsifiability requirement	Both a theory and a hypothesis must be falsifiable, meaning they can be proven wrong through testing or new evidence.
Explanatory purpose	A theory and a hypothesis both aim to explain why a phenomenon occurs rather than merely describing what happens.
Predictive capability	Both a hypothesis and a theory generate predictions about future observations or experimental outcomes that researchers can verify.
Subject to revision	A theory and a hypothesis are both provisional and can be modified, refined, or discarded when new evidence emerges.
Researcher use	Scientists use both a hypothesis and a theory to frame research questions, design studies, and interpret experimental results.
Logical reasoning	Both a theory and a hypothesis depend on deductive or inductive logical reasoning to connect concepts and derive expectations.
Variable relationships	A hypothesis and a theory both specify relationships between independent and dependent variables in a study.
Peer scrutiny	Both a theory and a hypothesis are evaluated by the scientific community through peer review, replication, and critical analysis.
Clear definitions	A theory and a hypothesis both require precisely defined terms and concepts to be tested and communicated effectively.
Boundary conditions	Both a hypothesis and a theory operate within specific conditions or contexts where their claims are expected to hold true.
Data interpretation	A theory and a hypothesis both guide how scientists interpret collected data and decide whether results are meaningful.
Research funding	Both a hypothesis and a theory often require financial support to conduct the experiments or observations needed for validation.
Publication potential	A hypothesis and a theory both can be published in scientific journals to share findings and invite community feedback.
Educational value	Both a theory and a hypothesis are taught in classrooms to help students understand how scientific knowledge develops over time.
Conceptual frameworks	A hypothesis and a theory both provide a structured framework for organizing knowledge and guiding further inquiry.
Measurement reliance	Both a theory and a hypothesis depend on measurable variables and quantitative or qualitative data to assess their validity.
Uncertainty acceptance	A theory and a hypothesis both acknowledge inherent uncertainty, and neither claims absolute, final truth about a subject.
Communication tools	Both a hypothesis and a theory serve as communication tools that let scientists share complex ideas with peers and the public.
Historical development	A hypothesis and a theory both evolve from prior knowledge, building on earlier research and existing scientific literature.
Methodological alignment	Both a theory and a hypothesis must align with established research methods to be properly tested and validated.
Error detection	A hypothesis and a theory both help researchers identify errors in reasoning, experimental design, or data analysis.
Replication support	Both a theory and a hypothesis encourage replication studies to confirm that findings are consistent across different samples and settings.
Long-term refinement	A theory and a hypothesis both undergo gradual refinement over years as new technologies and evidence become available.
Critical thinking	Both a hypothesis and a theory require critical thinking skills to evaluate assumptions, evidence quality, and alternative explanations.
Scope limitation	A theory and a hypothesis both have limited scope, and neither can explain every aspect of a phenomenon or all related observations.
Knowledge advancement	Both a hypothesis and a theory ultimately drive scientific progress by generating new questions, discoveries, and practical applications.

Theory or Hypothesis: Which Should You Choose?

Choose based on your evidence level. A theory explains a confirmed, repeatedly tested phenomenon. A hypothesis is a testable prediction you have not yet proven. If you have extensive supporting data, use theory. If you are starting an investigation, use hypothesis.

When to Use Theory

Choose Theory when you have decades of replicated, peer-reviewed evidence. Use it for established frameworks like evolution or germ theory. Apply it in final reports, textbooks, and expert discussions. Choose theory when your work explains why something happens, not just what might happen.

When to Use Hypothesis

Choose Hypothesis when you have a single untested prediction. Use it for new experiments, student projects, or early-stage research. Apply it when you need a falsifiable statement you can measure. Choose hypothesis when your data is limited or preliminary and you still need to run the test.

Common Misconceptions About Theory and Hypothesis

Common Myth	The Reality
A theory is just a guess that someone made up.	A theory is a well-tested explanation supported by vast evidence, while a hypothesis is the initial guess.
A hypothesis becomes a theory after one successful experiment.	A hypothesis becomes a theory only after years of repeated testing, peer review, and consistent evidence from many studies.
Theory and hypothesis are two words for the same thing.	A hypothesis is a testable prediction, whereas a theory is a comprehensive explanation that has survived rigorous testing.
Once proven, a hypothesis is permanently upgraded to a theory.	Science never proves anything absolutely; a hypothesis gains support, but a theory remains open to revision with new evidence.
In everyday talk, theory means an unproven idea.	In science, a theory is a robust explanation, but in casual language, theory often incorrectly means a mere guess.
A theory is weaker than a fact because it is uncertain.	A theory is a well-supported explanation of facts, and it carries more explanatory power than a single isolated fact.
You can call any random thought a hypothesis.	A hypothesis must be a specific, testable, falsifiable statement that predicts an outcome, not just any random thought.
Hypotheses are only used in science laboratories.	A hypothesis is used in any field with systematic inquiry, including psychology, economics, medicine, and social science research.
A theory can never be changed or overturned.	A theory can be revised or replaced when new evidence contradicts it, such as when new data refined older theories.
If evidence supports a hypothesis, it automatically becomes a law.	Supporting evidence strengthens a hypothesis, but a law describes patterns, while a theory explains why those patterns occur.
Hypotheses are always written as "if-then" statements.	Many hypotheses are if-then predictions, but some are directional or null hypotheses that state no expected relationship.
A theory is just an educated guess about a small detail.	A theory is a broad framework explaining many related phenomena, not a narrow guess about one small detail.
You need a hypothesis before you can observe anything.	Scientists often make observations first and then form a hypothesis to explain those initial observations.
Gravity is a theory, so it might not actually work.	The theory of gravity explains observed behavior, and its predictions are confirmed daily, so it reliably describes reality.
A hypothesis is a question that you want to answer.	A hypothesis is a declarative statement predicting an outcome, whereas a question is the research question that precedes it.
Evolution is just a theory, meaning scientists doubt it.	The theory of evolution is overwhelmingly supported by genetics, fossils, and observation, and it is not doubted by scientists.
Once a hypothesis fails, the whole research project is ruined.	A failed hypothesis still provides valuable data, and scientists often revise the hypothesis or design new tests.
All theories start as hypotheses and follow one fixed path.	Some theories emerge from mathematical models or observations without a single formal hypothesis, so the path varies.
A hypothesis must be proven true to be useful.	A hypothesis is useful if it is testable and falsifiable, even when the test results show the hypothesis is wrong.
Theory and hypothesis are interchangeable in academic writing.	Academic writing uses hypothesis for a prediction and theory for an explanatory framework, and mixing them causes confusion.
You can have a theory about one single event.	A theory explains general patterns across many events, whereas a hypothesis can address one specific predicted event.
Hypotheses are always proven or disproven with absolute certainty.	Hypotheses are supported or rejected based on probability and statistical evidence, never with absolute mathematical certainty.
A theory is the final step and no further research is needed.	A theory guides ongoing research, and scientists continually test its predictions to refine and expand its scope.
Beginners can test a hypothesis without any background knowledge.	Testing a hypothesis requires understanding the subject, variables, and methods, so background knowledge is essential for valid testing.
If a hypothesis is rejected, the original idea was worthless.	Rejecting a hypothesis eliminates a wrong path and sharpens the focus, so the idea still contributes to scientific progress.
Only theories can be used to make predictions.	Both a hypothesis and a theory make predictions, but a theory predicts across a wider range of related situations.
A hypothesis is always a single sentence with one variable.	A hypothesis can involve multiple variables and relationships, though it must remain specific and testable.
The word theory in science means the same as in law.	In law, a theory is a legal argument, but in science, a theory is an evidence-based explanation of natural phenomena.
You must publish a hypothesis before testing it.	Hypotheses are often tested first and then published with results, so pre-publication is not a requirement for testing.
A hypothesis is a theory that has not been tested yet.	A hypothesis is a specific testable prediction, while a theory is a broad explanation already supported by extensive testing.

Conclusion

Difference Between Theory and Hypothesis is scope and evidence. A hypothesis is a testable prediction awaiting verification. A theory is a well-substantiated explanation supported by extensive testing. Choose hypothesis when testing an idea. Choose theory when explaining established, repeatedly confirmed phenomena.

FAQs on Difference Between Theory and Hypothesis

What is the main difference between a theory and a hypothesis?: A theory is a well-tested, widely accepted explanation supported by extensive evidence, while a hypothesis is a specific, testable prediction that has not yet been confirmed.
Is a hypothesis a guess?: No, a hypothesis is an educated, testable prediction based on prior knowledge and observations, not a random guess, because it must be falsifiable through experimentation.
Which is better to have, a theory or a hypothesis?: Neither is inherently better, because a hypothesis serves as a starting point for investigation, while a theory represents a mature, validated explanation that has survived rigorous testing.
Does it cost more to test a hypothesis than to develop a theory?: Testing a hypothesis typically costs less per experiment, whereas developing a theory requires cumulative funding for many studies, so the total investment for a theory is usually higher.
What are the risks of treating a hypothesis as a theory?: The main risk is drawing premature conclusions, because an untested hypothesis lacks the evidence needed to guide decisions, which can lead to incorrect assumptions and wasted resources.
Can a hypothesis be compatible with an existing theory?: Yes, a hypothesis is often compatible with an existing theory when it makes a specific, testable prediction that fits within the broader theoretical framework.
What is a common beginner mistake when using the terms theory and hypothesis?: A common mistake is using them interchangeably in everyday speech, because this blurs the critical distinction between an unverified prediction and a well-established explanation.
Can the terms theory and hypothesis be used interchangeably in science?: No, they cannot be used interchangeably in science, because a hypothesis is a tentative proposal for testing, whereas a theory is a comprehensive explanation with strong supporting evidence.
What is a real-world use case for a hypothesis in a scientific field?: In medicine, a researcher uses a hypothesis to predict that a new drug reduces blood pressure, then designs a clinical trial to test that specific prediction before any theory is formed.
Can I switch from calling my idea a hypothesis to a theory?: Yes, you can switch only after your hypothesis has survived repeated testing and accumulated sufficient evidence to become a widely accepted explanation, not simply because you prefer the term.