There are different types of research hypotheses: the research or work hypothesis, the alternative hypothesis, the null hypothesis or the statistical hypothesis. A hypothesis is a probable, objective and specific answer to a scientific question, which must be tested.
However, it is possible for an investigation to have more than one hypothesis. This means that different types of hypotheses are also related to each other. For example, a research hypothesis can act as the main hypothesis in a work, but in turn the null, alternative and statistical hypotheses contribute to clarifying the central hypothesis.
What Are The Types of Research Hypotheses?
To understand this better, let’s look at each type of hypothesis separately and their respective variants (with examples).
Research or working hypothesis
The research hypothesis aims to answer what is the relationship established between various variables. It is also known as a working hypothesis. It constitutes the starting point of all scientific research.
According to its approach, it is divided into descriptive hypotheses, causal hypotheses, correlational hypotheses or group difference hypotheses.
They limit themselves to describing the relationship between the variables under study, but do not explain their causes. They anticipate the expected variable type, value and qualities.
For example , “Crime in the city of Caracas has increased 50% compared to 2019.”
Causal hypotheses or causality hypotheses are those that propose to explain the cause-effect relationship between two or more variables. They can be explanatory or predictive.
- Explanatory hypotheses. They offer a possible explanation about the cause that relates the variables. For example , “Excessive alcohol consumption causes neuronal damage.”
- Predictive hypotheses. They predict how one variable will behave in response to another. For example , “Global warming will cause flooding in the coming years.”
Both explanatory and predictive hypotheses can be formulated inductively or deductively. Let’s see.
- Deductive hypotheses: based on a theory, the researcher formulates a hypothesis to explain a specific case. That is, deductive hypotheses are formulated from the general to the particular. For example, “All living things have DNA. Bacteria are living beings. Therefore, bacteria have DNA.
- Inductive hypotheses: based on the observation of a specific case or phenomenon, the researcher formulates a generalization or general principle. That is, inductive hypotheses are formulated from the particular to the general.
For example , Newton observed that, although the Moon and the apple are two spherical bodies, only the apple falls to the ground. Capturing this specific difference allowed him to induce the existence of a law that explained said behavior. Thus, he hypothesized that there is a force of attraction (gravity) between bodies.
Correlational or joint variation hypotheses are those that establish the degree of mutual relationship between the variables, that is, how and to what degree one affects the other (and vice versa). In this type of hypothesis, the order of the variables is indifferent.
For example, Newton’s theory of gravity is a correlational hypothesis, since its statement dictates: “The greater the mass, the greater the force of attraction.” Correlationally, it follows that: “The greater the force of attraction, the greater the mass.”
Correlational hypotheses can be negative, positive or mixed.
For example ,
- Positive: “The greater the impunity, the greater the crime.”
- Negative: “The lower the consumption of fat, the lower the risk of suffering from coronary heart disease.”
- Mixed: “The higher the altitude, the lower the temperature.”
Group difference hypothesis
Group difference hypotheses are those that anticipate the difference in the behavior of various groups. It is based on statistical comparison. The group difference hypotheses are expressed in two variants:
- Those that establish a difference between two groups, without determining which group it falls on. For example , “There is a difference in mortality rates from covid19 between female and male people.”
- Those that determine which of the groups the difference falls on. For example , “The mortality rate from covid19 is higher in men than in women.”
The null hypothesis is one that denies the relationship between two or more variables based on a sample parameter. Its statement is negative, which means that it includes a “no.” It is represented by the symbol H 0 . The null hypothesis is not accepted, but rather rejected or not rejected.
The formulation of the null hypothesis is normally accompanied by the formulation of an alternative hypothesis that seeks to demonstrate its falsehood.
For example , “Muscle mass index is not associated with people’s sex.”
Every null hypothesis generates an alternative hypothesis, that is, an alternative answer to the null hypothesis that aims to demonstrate its falsehood. It is represented by the symbol H 1 . This type of hypothesis is accepted or not accepted.
For example ,
- H 0 : «The muscle mass index is not associated with the sex of the people»
- H 1 : «The muscle mass index differs between men and women».
Statistical hypotheses are those that translate hypotheses into statistical symbols. Seek to affirm or define the parameters of one or more populations. Therefore, they are formulated whenever data is expected to be collected in numbers, percentages or averages.
They are subdivided into:
- estimation hypotheses , which deal with descriptive hypotheses of a single variable. This is analyzed in context. The researcher formulates a statistical estimate of the result.
- statistical correlation hypotheses , which deal with correlation hypotheses, which are those that study the relationship between two or more variables.
- statistical hypotheses of mean differences , which deal with the difference between groups. Compare numerical estimates between two or more groups in analysis.
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