Types of Hypotheses (Meaning and Explanation)

We explain what types of hypotheses exist and the characteristics of descriptive, causal, correlational and more.

What is a hypothesis?

a hypothesis It is a proposition or statement that we wish to corroborate or contradict, through research. In other words, a hypothesis is an idea that we presuppose and that we wish to subject to the rigor of a research method, such as the scientific method, for example, or that we wish to test through experience.

Hypotheses are provisional, tentative statements, which may or may not turn out to be true and demonstrable, but from the outset They help us establish what we want to investigate and they allow us to find our ideal verification method. Therefore it is said that the hypothesis is the link between theory and observation. Every investigation, therefore, necessarily begins with the formulation of a hypothesis.

However, it is possible that an investigation raises more than one hypothesis, and that these are of a different nature. Logically, some of them will turn out to be valid (when proven), while others will turn out to be invalid (when refuted). But below we will see a more or less general classification of the hypotheses.

Types of hypotheses

Descriptive hypotheses

Those that They establish the relationship between the variables that are being studied, without worrying about their causes and without establishing comparisons. between them. They are limited, as their name indicates, to describing and anticipating the variables, values and qualities of the matter.

As an example, suppose that a group of scientists studies the recurrence of a disease in the population of their country. They decide, as a working hypothesis, to assume that the disease is distributed equally among all ethnic groups that make up the total population, but as they complete their research, they realize that some ethnic groups are more affected than others.

Correlational hypotheses

Also called joint variation, which, as its name indicates, propose a correlation between the variables studied, that is, they propose the way and degree to which one affects the other. Depending on how this relationship is, these hypotheses can be of three types:

Positive correlation hypothesiswhen the increase of one variable brings with it the increase of the other. For example, if scientists who study the disease propose that the older the patients are, the greater the chance of death when infected.
Negative correlation hypothesiswhen the decrease in one variable brings with it the decrease of the other. For example, if scientists who study the disease propose that there are fewer infected patients when the age of the population is lower.
Mixed correlation hypothesiswhen the increase or decrease of one variable brings with it a decrease or increase, respectively, of the other. For example, if scientists who study the disease propose that earlier treatments result in fewer deaths from the disease.

Causal hypotheses

Those that explore the cause-effect relationship between the variables studied, proposing some type of specific meaning. Depending on what this meaning is, we can talk about:

Explanatory hypotheseswhich propose a verifiable cause and effect relationship between the variables, so that one can be explained by the other. For example, returning to the case of the disease that scientists study, once it has been proven that it does not affect all ethnic groups equally, they could hypothesize that the disease affects people of a certain ethnicity more because they have in greater abundance of a specific protein in the blood.
Predictive hypotheseswhich propose a probable cause and effect relationship between the study variables, projecting it into the future. For example, again with the case of the disease studied, scientists could hypothesize that the greater affectation of certain sectors of the population will soon cause a change in the genetics of the infectious agent.

Statistical hypotheses

Those that refer to sets of variables and express their relationships in percentage or proportional terms, instead of absolute terms. They are very common in probabilistic, population or predictive studies. This type of hypothesis can be classified, at the same time, into:

Statistical estimation assumptionswhich allow the researcher to evaluate the value of some statistical variable in relation to a population and a set of prior information. For example, if scientists investigating the disease propose that, of infected patients, 70% present a certain symptom, therefore this should be considered a main symptom.
Statistical correlation hypotheseswhich seek to propose in statistical terms some correlation between the variables. For example, if scientists investigating the disease consider that its mortality has mainly to do with the socioeconomic level of the patients, since 80% of serious cases come from popular neighborhoods.
Statistical hypotheses of differentiation of meanswhich propose a relationship between the statistics of two human groups. For example, if scientists who study the disease consider that men are 40% more likely than women to suffer from it.

Null hypotheses

A null hypothesis is one that refutes what was established in a research hypothesiswhatever the type of the latter. Therefore, null hypotheses are the reverse of research hypotheses, and can be of the same type as any of them (any of the ones we have listed so far).

For example, if scientists who study the disease seek to demonstrate that its severity has nothing to do with the sex of the patients.

Inductive, deductive and analogy hypotheses

Any of the previous hypotheses can be of an inductive, deductive or analogous type, based on the logic that serves to establish the relationship between the variables studied. This is expressed in the very way of presenting the relationship, in the following way:

Deductive hypotheses or that operate by deductionthose that propose a relationship from the general to the particular, using other previous hypotheses that have already been demonstrated as a starting point. For example, if scientists who study the disease verify that it affects a certain ethnic group more than another, they can then deduce that it affects those who have a certain genetic component more, since the latter is dominant in said ethnic group.
Inductive hypotheses or that operate by inductionthose that propose a relationship from the particular to the general, that is, contrary to deductive ones, based on intuition from what is observed. For example, if scientists studying the disease do not find any serious cases among people of a certain ethnicity, they may consider that there is a genetic component to it that makes them immune.
Analogous hypotheses or that operate by analogythose that propose a relationship between the variables inspired, copied or transferred from another field of knowledge in which it was verified. That is, they assume that if said hypothesis was valid in another field, it may also be valid in theirs. For example, if scientists studying the disease consider that, since a different but similar disease was treated with a specific antibiotic, it is possible that this new disease responds in the same way.

References

“Hypothesis (scientific method)” on Wikipedia.
“The hypothesis: a link for research” at the Autonomous University of the State of Hidalgo (Mexico).
“Research methodology” by Cristian Rusu at the Catholic University of Valparaíso (Chile).