How to Formulate a Hypothesis - Guide

The hypothesis is one of the most misunderstood concepts in thesis writing. Many people think it's just a formal requirement to include at the beginning and then forget about. Others overcomplicate it, spending days formulating the "perfect" hypothesis.

The truth lies somewhere in between: a hypothesis is important because it gives direction to your research, but you don't need to be afraid of it. In this article, I'll explain exactly what a hypothesis is, how to formulate it correctly, and provide plenty of concrete examples you can use as a starting point.

What you'll learn from this article:

✓ What a hypothesis is and why it's important in a thesis
✓ Types of hypotheses (null hypothesis, alternative hypothesis, directional/non-directional)
✓ The 6 criteria of a good hypothesis
✓ Step-by-step guide to formulating your hypothesis
✓ 30+ concrete hypothesis examples from different academic fields
✓ Most common mistakes and how to avoid them

What is a Hypothesis?

Let's start with the basics. A hypothesis is a well-founded assumption or preliminary statement that you will test during your research. Put simply: it's what you think will emerge from the research, before you actually begin.

The keyword here is "well-founded." A hypothesis is not a random guess or hunch – it's a statement that:

You formulate based on existing literature
Can be logically derived from theoretical background
Is testable through empirical methods
Can be either confirmed or refuted

A simple example

Let's say your thesis topic is the effect of social media on young people's self-esteem. In the literature, you read that several studies found a correlation between Instagram use and lower self-esteem.

"More intensive Instagram use negatively affects the self-esteem of women aged 18-25."

This is a hypothesis. You don't know for sure if it's true – your research will find out.

What's the Difference Between a Hypothesis and a Research Question?

This is one of the most common sources of confusion. Many people mix them up, but they serve different purposes:

Research Question	Hypothesis
Phrased as a question	Phrased as a statement
Open – no predetermined answer	Closed – formulates a specific expected answer
Sets the direction of research	Formulates the testable claim of research
Every research has one	Mainly used in quantitative research

Same topic, different formulations:

Research Question: "How does Instagram use affect the self-esteem of young women?"

Hypothesis: "More intensive Instagram use negatively affects the self-esteem of women aged 18-25."

Types of Hypotheses

Not all hypotheses are the same. Knowing the types helps you choose the right one for your research.

1. Null Hypothesis (H₀)

The null hypothesis states that there is no relationship or no difference between the variables being studied. This is the starting point for statistical testing – your research attempts to refute this.

Examples of null hypotheses:

"There is no significant difference between men's and women's salaries in the same position."
"The introduction of remote work does not affect employee productivity."
"Online marketing does not influence consumer purchasing decisions."

2. Alternative Hypothesis (H₁ or Hₐ)

The alternative hypothesis states that there is a relationship or is a difference. This is what we usually want to "prove" – if we can refute the null hypothesis, we accept the alternative hypothesis.

Examples of alternative hypotheses:

"There is a significant difference between men's and women's salaries in the same position."
"The introduction of remote work affects employee productivity."
"Online marketing influences consumer purchasing decisions."

3. Directional (One-Tailed) Hypothesis

A directional hypothesis not only states that there is a relationship, but also specifies its direction. It indicates whether the effect is positive or negative, represents an increase or decrease.

Examples of directional hypotheses:

"Women's salaries are lower than men's in the same position."
"The introduction of remote work increases employee productivity."
"More social media use decreases sleep quality."

4. Non-Directional (Two-Tailed) Hypothesis

A non-directional hypothesis states that there is a relationship, but does not specify its direction. Use this when the literature doesn't make the direction of the effect clear.

Examples of non-directional hypotheses:

"There is a difference between men's and women's salaries in the same position."
"The introduction of remote work affects employee productivity."
"There is a relationship between social media use and sleep quality."

Which should you choose?

If the literature clearly points in one direction, use a directional hypothesis – it's a stronger claim and statistically easier to test. If the results are mixed or there isn't enough research, stick with a non-directional hypothesis.

The 6 Criteria of a Good Hypothesis

How you formulate your hypothesis matters. A good hypothesis is:

1. Testable

This is the most important criterion. Your hypothesis must be empirically testable – supportable or refutable with data. If you can't say what data you would use to test it, it's not a good hypothesis.

Bad: "Happiness is important in life." (How would you test this?)

Good: "Regular weekly exercise positively correlates with life satisfaction levels."

2. Specific

The hypothesis needs to be concrete and clear. Avoid general formulations.

Bad: "Technology influences education."

Good: "The use of interactive whiteboards increases the classroom engagement of 7th-8th grade students in mathematics."

3. Measurable

You need to be able to operationalize the concepts in your hypothesis – that is, specify exactly how you will measure them.

Bad: "Good leaders are more successful."

Good: "Teams led by leaders with high emotional intelligence achieve 15% higher customer satisfaction scores."

4. Relevant

The hypothesis must relate to your research question and thesis topic. It cannot be too broad or point in a completely different direction.

5. Well-Founded

Your hypothesis doesn't come from nowhere – you need to derive it from the theoretical background and previous research. In the introduction or theoretical section, you need to justify why you're proposing this particular hypothesis.

6. Falsifiable

The hypothesis must be falsifiable. If no matter what happens, you consider it "proven," that's not a scientific hypothesis.

Bad: "Consumer behavior is influenced by many factors." (This cannot be refuted)

Good: "Price promotions significantly increase the number of impulse purchases."

How to Formulate a Hypothesis – Step by Step

Now that you know the theoretical foundations, let's see how to apply them in practice.

Step 1: Define Your Research Question

Before formulating a hypothesis, clarify exactly what you want to find out. The research question will be the foundation of everything.

"How does employee benefits packages affect job satisfaction in the IT sector?"

Step 2: Review the Relevant Literature

Look at what previous research has found. What do the theories say? What relationships have others discovered? This provides the foundation for your hypothesis.

Step 3: Identify the Variables

Determine:

Independent variable: what you change or whose effect you examine (e.g., quality of benefits package)
Dependent variable: what you examine the effect on (e.g., job satisfaction)

Step 4: Formulate the Statement

Based on the literature, formulate what relationship you expect between the variables.

"A more comprehensive benefits package positively affects job satisfaction among IT sector employees."

Step 5: Check Against the Criteria

Review the 6 criteria:

Testable? Yes, both variables can be measured with surveys.
Specific? Yes, defined sector and variables.
Measurable? Yes, both benefits package and satisfaction can be operationalized.
Relevant? Yes, it relates to the topic.
Well-founded? Yes, derivable from the literature.
Falsifiable? Yes, if there's no relationship, we refute it.

Step 6: Refine if Necessary

If any criterion isn't met, modify the hypothesis. Usually specificity and measurability cause problems – in such cases, clarify the variables or target group.

30+ Hypothesis Examples by Academic Field

Now for the main part: concrete examples you can draw inspiration from. These aren't "ready-made" hypotheses – adapt them to your own research!

Marketing and Business

H1: "The use of influencer marketing increases brand awareness among the 18-25 age group."

H2: "Personalized email campaigns result in higher conversion rates than generic newsletters."

H3: "Positive online customer reviews significantly increase purchase intention."

H4: "Sustainability communication positively influences premium pricing acceptance among Generation Z."

H5: "Mobile-first web design reduces cart abandonment rates in e-commerce."

Finance and Accounting

H1: "ESG investment returns do not significantly lag behind traditional investments."

H2: "High financial literacy positively correlates with household savings rates."

H3: "The use of fintech applications increases young people's financial awareness."

H4: "Corporate CSR activities positively influence stock prices."

HR and Organizational Psychology

H1: "The use of flexible working hours reduces employee turnover."

H2: "A structured onboarding program increases the 90-day retention rate of new employees."

H3: "Transformational leadership style positively correlates with team performance."

H4: "Employee wellbeing programs reduce the number of sick leave absences."

H5: "Regular feedback positively influences employee engagement."

IT and Computer Science

H1: "The introduction of two-factor authentication reduces the number of successful cyberattacks."

H2: "The use of agile methodologies increases the success rate of software development projects."

H3: "Cloud-based infrastructure reduces IT operational costs for SMEs."

H4: "User-friendly UI design increases application user retention rates."

Tourism and Hospitality

H1: "Social media presence positively influences accommodation occupancy rates."

H2: "Environmentally conscious services increase guest return intentions."

H3: "The introduction of online booking systems increases restaurant revenue."

H4: "Offering local culinary experiences increases tourists' average spending."

Education and Pedagogy

H1: "Gamified teaching methods increase student motivation."

H2: "Smaller class sizes positively correlate with academic performance."

H3: "Project-based learning develops critical thinking skills."

H4: "The use of digital tools increases classroom participation."

Healthcare and Nursing

H1: "Patient education programs reduce readmission rates for chronic disease patients."

H2: "Flexible shift scheduling reduces the burnout rate among nurses."

H3: "The use of telemedicine increases patient compliance."

How Many Hypotheses Should a Thesis Have?

This is one of the most common questions, and unfortunately, there's no universal answer. It depends on the university, the field, the topic, and the type of research.

Some guidelines:

Undergraduate (BA/BSc) thesis: typically 2-4 hypotheses
Graduate (MA/MSc) thesis: typically 3-6 hypotheses

Important!

You need to test every hypothesis in your research. It's better to have fewer well-developed ones than many superficial ones. If you state 5 hypotheses, you need to collect and analyze data for all 5.

Most Common Mistakes in Hypothesis Formulation

1. Too General Formulation

"Marketing is important for companies" type statements are not hypotheses, but general observations. Be specific!

2. Untestable Statements

If you can't explain how you would test it, it's not a good hypothesis. Every hypothesis should have a clear indication of what data you'll use to examine it.

3. Value Judgments

"Sustainable development is better than traditional" type statements are value judgments, not scientific hypotheses.

4. Already Proven Statements

If a relationship has been proven countless times, there's not much point in testing it again (unless you're examining it in a different context).

5. Too Many Variables at Once

A hypothesis should preferably examine one relationship. If you try to cram too many variables in, it will be difficult to test and interpret.

Summary

A hypothesis is nothing more than a well-founded assumption that you test with your research. Don't be afraid of it – if you follow the steps and adhere to the criteria, you'll formulate a good hypothesis.

Key takeaways:

✓ A hypothesis is a testable statement formulated in declarative form
✓ It should be specific, measurable, relevant, and falsifiable
✓ Base it on literature – don't pull it out of thin air
✓ Identify the independent and dependent variables
✓ Don't have too many – you need to test every hypothesis
✓ At the end of the research, verify (confirmed or refuted)

Now you're ready to formulate your own hypothesis. If you get stuck, check out our other articles on research methodology!