There are different types of hypotheses in scientific research . From the null hypothesis, general or theoretical, to complementary, alternative or working hypotheses.

What is a hypothesis?

But, what exactly is a hypothesis and what is it for? Hypotheses specify the possible characteristics and results that may exist among certain variables that are going to be studied.

Using the scientific method, a researcher should try to verify the validity of his or her initial (or main) hypothesis. This is often called a working hypothesis. At other times, the researcher has several complementary, or alternative, hypotheses in mind.

If we examine these working hypotheses and alternatives we find three subtypes: attributive, causal and associative hypotheses. The general or theoretical hypotheses serve to establish a relationship (negative or positive) between the variables, while the working and alternative hypotheses are those that effectively quantify this relationship.

On the other hand, the null hypothesis is that there is no appreciable link between the variables studied. In the event that it is not possible to check that the working hypotheses and alternative hypotheses are valid, the null hypothesis is accepted as correct.

Although those mentioned are considered the most common types of assumptions, there are also relative and conditional assumptions. In this article we will discover all types of hypotheses, and how they are used in scientific research.

What are hypotheses for?

Any scientific study must be initiated taking into account one or several hypotheses that are intended to be confirmed or refuted.

A hypothesis is nothing more than a conjecture that may or may not be confirmed by scientific study. In other words, hypotheses are the scientists’ way of posing the problem, establishing possible relationships between variables.

Types of hypotheses used in a scientific study

There are several criteria that can be followed when classifying the types of hypotheses used in science. We’ll get to know them below.

1. Null hypothesis

The null hypothesis refers to the fact that there is no relationship between the variables that have been investigated . It is also called “null hypothesis”, but should not be confused with a negative or inverse relationship. Simply put, the variables studied do not seem to follow any specific pattern.

The null hypothesis is accepted if the scientific study results in the working hypotheses and alternatives not being observed.

Example

“There is no relationship between people’s sexual orientation and their purchasing power.”

2. General or theoretical hypotheses

The general or theoretical hypotheses are those that scientists establish prior to the study and conceptually , without quantifying the variables.
Generally, the theoretical hypothesis is born from processes of generalization through certain preliminary observations about the phenomenon they wish to study.

Example

“The higher the level of education, the higher the salary.”
There are several subtypes within the theoretical hypotheses. The difference hypotheses, for example, specify that there is a difference between two variables, but do not measure their intensity or magnitude. Example: “In the School of Psychology there are more students than there are students”.

3. Working hypothesis

The working hypothesis is the one used to try to demonstrate a concrete relationship between variables through a scientific study.
These hypotheses are verified or refuted by means of the scientific method, which is why they are sometimes also known as “operational hypotheses”.
Generally, working hypotheses are born from deduction: from certain general principles, the researcher assumes certain characteristics of a particular case. Working hypotheses have several subtypes: associative, attributive and causal.

3.1. Associative

The associative hypothesis concretizes a relationship between two variables. In this case, if we know the value of the first variable, we can predict the value of the second one.

Example

“There’s twice as many students in the first year of high school as in the second.”

3.2. Attributive

The attributive hypothesis is the one used to describe the events that occur between the variables. It is used to explain and describe real and measurable phenomena. This type of hypothesis only contains one variable.

Example

“Most homeless people are between 50 and 64 years old.”

3.3. Causal

The causal hypothesis establishes a relationship between two variables. When one of the two variables increases or decreases, the other is increased or decreased. Therefore, the causal hypothesis establishes a cause-and-effect relationship between the variables studied.
To identify a causal hypothesis, a cause-effect link, or statistical (or probabilistic) relationship, must be established. It is also possible to verify this relationship through the refutation of alternative explanations. These hypotheses follow the premise: “If X, then Y”.

Example

“If a player trains for an additional hour each day, his success rate on throws increases by 10%.”

4. Alternative hypotheses

The alternative hypotheses try to offer an answer to the same question as the working hypotheses . However, as can be deduced from its name, the alternative hypothesis explores different relationships and explanations. In this way, it is possible to investigate different hypotheses during the course of the same scientific study.
This type of hypothesis can also be subdivided into attributive, associative and causal.

More types of hypotheses used in science

There are other types of hypotheses that are not so common, but which are also used in different types of research. They are as follows.

5. Relative assumptions

Relative assumptions give evidence of the influence of two or more variables on another variable.

Example

“The effect of the decline in per capita GDP on the number of people in private pension schemes is less than the effect of falling public expenditure on the rate of child malnutrition”.

  • Variable 1: decrease in GDP
  • Variable 2: fall in public expenditure
  • Dependent variable: number of persons having a private pension plan

6. Conditional hypotheses

Conditional assumptions are used to indicate that a variable depends on the value of two other variables . This is a type of hypothesis very similar to the causal ones, but in this case there are two variables “cause” and only one variable “effect”.

Example

“If the player receives a yellow card and is also warned by the fourth referee, he shall be excluded from play for 5 minutes”.

  • Cause 1: receive yellow card
  • Cause 2: being warned
  • Effect: being excluded from the game for 5 minutes.
    As we can see, for the “effect” variable to occur, not only one of the two “cause” variables must be met, but both.

Other types of hypotheses

The types of hypotheses we have explained are the most commonly used in scientific and academic research. However, they can also be classified on the basis of other parameters.

7. Probabilistic hypotheses

This type of assumption indicates that there is a probable relationship between two variables . That is, the relationship is fulfilled in most of the cases studied.

Example

“If the student does not spend 10 hours a day reading, he will (probably) not pass the course.”

8. Deterministic hypotheses

Deterministic assumptions indicate relationships between variables that are always fulfilled , without exception.

Example

“If a player doesn’t wear boots with cleats, he can’t play the game.”

Bibliographic references:

  • Hernández, R., Fernández, C., and Baptista, M.P. (2010) Research Methodology (5th Ed.). Mexico: McGraw Hill Education
  • Salkind, N.J. (1999). Research Methods. Mexico: Prentice Hall.
  • Santisteban, C. and Alvarado, J.M. (2001). Psychometric models. Madrid: UNED