Research Methodology: Hypothesis
The article ‘Research Methodology: Hypothesis’ is covering the concept of a hypothesis, different forms of hypothesis, and the importance of hypothesis testing. Hypothesis testing is used to identify the variance in the group of data that results from the stance as created by the researcher post-researching the problem. The hypothesis can be divided into many categories.
What is a hypothesis?
A hypothesis is described as a formal statement that explains the relationship between two or more variables belonging to the specified population. It aids the researcher in converting the stated issue into an understandable justification for the study’s findings. It explains and foretells the anticipated result in unambiguous terms. It provides examples of various experimental designs and guides the study of the research procedure.
Nature of Hypothesis
A Hypothesis is a primary tool which is often used in research. Its main function is to recommend new experiments and observations. Typically, when one talks about a hypothesis, one simply means a single assumption or some presumption to be proved or disproved. Nonetheless, a hypothesis for a researcher is a formal query that he intends to answer. As a result, a hypothesis can be described as a claim or set of claims made as an explanation for the occurrence of a particular group of phenomena. These claims may be made solely as a provisional conjecture to direct an investigation, or they may be accepted as highly probable in light of existing facts. A research hypothesis is often a prediction that may be verified using evidence from science and that connects an independent variable to a dependent variable. The following are the key characteristics of the hypothesis:
1) It is conceptual. Some kind of conceptual elements in the framework is involved in a hypothesis.
2) It is a declarative statement made verbally. It is a verbal Expression of thoughts and concepts, it is not only a notion but in the verbal form, the idea is ready enough for empirical proof.
3) The empirical referent is present. There is some empirical reference in a theory. The tentative link between two or more variables is indicated.
4) It has a forward or future reference. A hypothesis is focused on the future. It relates to future verification, not past facts and information.
5) It is the pivot of scientific research. All the research activities are aimed towards its verification.
By distinguishing between a hypothesis and other concepts like assumption and postulate, the essence of the hypothesis may be better understood.
Importance & Use of Hypothesis
The Hypothesis contains various underlying benefits such as:
- It assures that complete study procedures remain scientific and valid.
- It helps to assume the chance of research failure and development.
- It helps to offer a link to the underlying theory and specific research question.
- It assists in data analysis and measures the validity and reliability of the research.
- It gives a basis or evidence to show the validity of the research.
- It helps to describe the research studies in concrete terms rather than theoretical terms.
Sources of Hypothesis
There are various sources of speculation but some of the significant ones are provided as follows:
1) Prior research: It will be very beneficial to develop a specific hypothesis if you have prior knowledge and information on the subject.
2) Personal experience: If one has a personal experience with the topic of inquiry, he/she can utilize such knowledge in the hypothesis to make it more full and good quality.
3) Thinking and Imagination: A researcher’s imaginative and creative thinking skills might occasionally help with the creation of a solid hypothesis. The personal thoughts and reasoning skills of a researcher would lead to a bigger number of hypothesis formulations and more control over the issue.
4) Scientific theory: It would be incredibly beneficial to apply scientific theories in hypothesis since it is capable of explaining all the facts related to the investigation.
Relationship between Variables and Hypothesis
Variables are measurable traits or properties of individuals or objects that can take on different values. The opposite of qualities that change are constants. A hypothesis states an assumed link between two variables in a way that may be tested with actual data. It may take the form of a cause-effect statement, or “if x, then y” statement.
The independent variable is the cause, and the dependent variable is the result.
Relationships come in both linear and non-linear varieties. Linear relationships can be either direct (positive) or inverse (negative) (negative). The values of the two variables rise or fall simultaneously when there is a direct or positive relationship between them. That is, if one increases in value, so does the other; if one drops in value, so does the other.
The values of the variables shift in opposite directions when there is an inverse or negative relationship. That is, if the independent variable increases in value, the dependent variable lowers; if the independent variable falls in value, the dependent variable increases. There is no simple method to explain how changes in the values of the independent variable affect changes in the values of the dependent variable in a non-linear relationship.
Types of Hypothesis
For easier comprehension let us understand some of the types of hypotheses to analyse how they are different from one another:
1. Null Hypothesis
Due to any experimental or sampling error, the null hypothesis states that there is no discernible difference between the populations mentioned in the trials. The null hypothesis is indicated by H0.
2. Empirical Hypothesis
Based on the results of the research that is thereby conducted by the researcher, an empirical hypothesis is developed.
3. Statistical Hypothesis
In a statistical hypothesis, the statement should be logical or illogical, so that the involved hypothesis can be verified statistically.
4. Alternative Hypothesis
An alternate theory states that random causes can easily affect basic observations. Ha or H1 is used to indicate it.
5. Complex Hypothesis
When there is a link between the existing variables, a complicated hypothesis is used. The dependent and independent variables in this hypothesis both have more than two components.
Formulating a Good Hypothesis
Developing an effective hypothesis starts before you even begin to type. Like with any endeavour, preparation is vital, so you begin by doing your research and reading as much as you can on the subject you intend to study. From there, you will get the information necessary to comprehend where your concentration will fall inside the subject. An effective research hypothesis is written succinctly and clearly, with any terminology or definitions being defined and clarified. To prevent making any assumptions or using generalisations, specific terminology must also be used.
Characteristics of a good hypothesis
Further, the points provided below can assist in re-checking the hypothesis to maintain its good quality:
- The language must be clear and focused
- There must be no ambiguity either in the language or in the essence of the meaning of the hypothesis thus formed
- There must be a ‘research and outcome’ relationship depicted from the hypothesis
- Manipulation of variables must be able to be done without hampering any standards of research
- The research must be testable and observable
- There must be sufficient relevancy of the research problem and question
- There must be a valid relationship between your research and your hypothesis
- Independent and dependent variables should be there in the hypothesis
Hypothesis testing is an act in statistics whereby an analyst examines an assumption on a population parameter. The approach adopted by the researcher depends on the nature of the data used and the reason for the analysis.
Using sample data, hypothesis testing is done to determine whether a claim is plausible. This data could originate from a broader population or a process that creates data. The word “population” will be used for both of these cases in the following descriptions.
In simple words, hypothesis testing can be understood to be the process of finalising whether the assumptions as were made before beginning the research are true or false. It is important to note that in case the null hypothesis is proven false then an alternate hypothesis is accepted. It does not mean that if the hypothesis comes out to be false then the research is incorrect. It would just imply acceptance of the alternate hypothesis.
Errors in Hypothesis Testing
Let us understand Type I and Type II errors in hypothesis testing:
Type I Error
A type I error happens when the null hypothesis (H0) of an experiment is true, yet still, it is rejected. It is stating something which is not present or a false hit. A false positive is a common term for a type I mistake (an event that shows that a given condition is present when it is absent). In folklore, if the null hypothesis (H0) contains the phrase “There is no bear,” then a person might see the bear when there is none (raising a false alarm).
Type II Error
When the null hypothesis is incorrect but is mistakenly not rejected, a type II error occurs. To say what is present and what is missing is losing. A type II error is also known as a false negative (when an actual hit was rejected by the test and is viewed as a miss), in an experiment checking for a condition having an outcome of true or false.
These are the two most common types of errors encountered in hypothesis testing.
 Priyanka Waghmare, ‘Research Hypothesis: Know about Type 1 and Type 2 Error’, Available Here
 Methods of Educational Research, Available Here
 ‘What is Hypothesis?’, Available Here
 ‘How to Write a Great Hypothesis’, Available Here
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