The formulation of the hypothesis is one of the steps of the scientific method. It is the part in which the researcher generates an assumption that will later be confirmed or rejected once the research goes through experimentation and analysis of results.
The use of the term hypothesis within the scientific research process dates back to the 19th century, when the pioneering ideas of the historian William Whewell and the influence of renowned thinkers such as Hegel, Comte and Engels, provided the frame of reference called the scientific method.
However, it is possible that from the work of the French doctor Claude Bernard, three stages differ in experimental research: observation, hypothesis and verification.
For Bernard, ordered thinking is necessary in scientific work, as well as creating experimental strategies, all this determined by a method. Thus, any researcher is forced to pose one or more hypotheses, which once contrasted will allow the conception of scientific knowledge.
What is a hypothesis?
The term hypothesis is of Greek origin, it comes from "hypóthesis" which means supposition, which in turn is derived from hiccups: low, and from thesis: conclusion. According to its etymology, the hypothesis is an apparent concept that is based on certain circumstances that support it. It is that tentative explanation that helps a researcher or scientist find a truth.
A hypothesis allows relationships between variables to be established and thus explain why something happens. They are fundamental for an investigation, since new theories can emerge from them, always based on an adequate theoretical framework. Hypotheses indicate that you have to start from what exists to arrive at something new.
What is the hypothesis formulation of the scientific method?
Any researcher goes through at least two basic stages.
The first, when he makes a careful observation that allows him to see the reality and the totality of concrete facts that surround the phenomena to be studied.
The second, when based on what has been observed, formulates a hypothesis, which, subject to timely verification, provides him with sufficient data or information to approve or reject it.
Both stages are important, but the formulation and subsequent testing of hypotheses are the maximum point in the generation of scientific knowledge.
When formulating a hypothesis, the researcher does not have the total certainty of being able to verify it, therefore it is undergoing a rectification process in order to improve itself in the face of the scientific method. A hypothesis must be able to be tested to see if it is true.
At the end of a study the hypotheses will have been in conclusion, rejected, approved, or replaced by new hypotheses.
The hypothesis is of great importance for the scientific method because it helps to propose possible solutions for a given problem.
How is a hypothesis made?
To make a hypothesis it is important that it is specific, so that the signals to be used to measure the variables studied are determined.
Therefore, the hypothesis should contribute to the explanation of the facts studied from the relationships it makes between variables.
Variables
They can be defined as everything that manages to assume different values, from the quantitative or qualitative point of view or everything that is going to be measured, examined and studied in an investigation. Therefore, they are capable of measurement.
They are changing characteristics and, precisely, that variability is what the researcher measures or analyzes.
When writing a hypothesis, it must be taken into account in an affirmative, unambiguous manner and must include the elements of the problem investigated with its variables and approaches.
To state scientific hypotheses, basic rules must be followed, they must give the essence of what you want to define, be affirmative, and use clear language.
Although many think otherwise, the biggest mistake in making a hypothesis is thinking that this is the first step of the investigation, because for no reason it is.
Steps to formulate a hypothesis
1 - Group information
2 - Compare the information gathered
3 - Provide probable explanations
4 - Choose the most feasible explanation and
5 - Formulate one or more hypotheses.
After doing all these steps comes experimentation, in which the validity of the hypothesis is confirmed.
If the hypothesis is proved, then what is hypothesized is true. In case it is not confirmed, the hypothesis will be false.
In this case, another hypothesis must be formulated with the actual data that has been obtained.
Examples of hypotheses
A useful hypothesis should allow predictions by reasoning, including deductive reasoning . You could predict the outcome of a laboratory experiment or the observation of a phenomenon in nature. Prediction can also be statistical and deal only with probabilities.
Some examples of hypotheses are:
- Soccer players who train regularly with the use of time, score more goals than those who miss 15% of days to training.
- First-time parents who have studied higher education are in 70% of the most relaxed cases in childbirth.
- Vegans who take vitamin b12 will be less likely to develop anemia.
- A daily use of lye in the toilet could eliminate up to 95% of microbes and 65% of bacteria.
- If following the Mediterranean diet I have lost 1 kg. in one week, in four weeks I will lose 4 kg.
It should be remembered that these are only examples of hypotheses, many of them being invented, so they lack scientific rigor.
Types of hypotheses
There are many types of hypotheses, but we will base ourselves on the following:
1 - Research hypothesis
They are those proposals about the possible relationships between two or more variables. They are statements that researchers make when they speculate about the result of an investigation or experiment. Within these there are different classes:
- Descriptive hypotheses : they are used in descriptive studies, they indicate the existence of an event, the variables are taken from a certain context where they can be observed.
- Correlational hypotheses: they involve the evaluation between variables and if any of them undergoes any change, it will affect the others. They reach the predictive and explanatory level, since knowing which two concepts or variables are related in a certain way, provides explanatory information. The order in which we place the variables is not important.
- Hypotheses of differences between groups: they seek to determine the differences between groups, they do not necessarily establish why these differences occur.
- Hypotheses that establish causal relationships: they affirm that there are relationships between two or more variables, how these relationships occur and also propose a sense of understanding of them. All of these establish cause-effect relationships.
2 - Null hypotheses
A null hypothesis is a type of hypothesis used in statistics that proposes that there is no statistical significance in a given set of observations.
3 - Alternative hypotheses
They are alternatives to the research and null hypotheses. They offer different explanations than the ones they provide.
They can only be formulated when there are indeed additional possibilities to the research and null hypotheses.
4 - Statistical hypotheses
They are the transformation of research hypotheses, null and alternative in statistical terms.
They can only be formulated when the study data to be collected and analyzed to test the hypotheses is quantitative.
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