This blog article will take you through all the important elements you need to know about while developing your research hypothesis.

As a research student, you know a dissertation and a thesis are not a piece of cake and there's certainly no cherry on the top.

Even thinking of the beginning one gives you chills. But as a research professional, your typical day at work is filled with new research development every single day.

You must be wondering how researchers pull off a research paper almost every week and work on so many different research and development projects at the same time while you struggle with one for months.

The answer is no researcher has it all together every time. Professional researchers also suffer from so many dead ends and idea blocks that lead nowhere and waste a lot of precious time.

However, every researcher focuses on having a few elements sorted to have clarity at all times. These elements are the main research question or problem, the purpose of the research, and lastly the hypothesis.

These three elements are the very first roadblock in the way of having a smooth road ahead to the final research.

Now while the research question or problem and the purpose of the research are always given a lot of importance, the hypothesis is just as crucial.

Now you must be wondering how something like a hypothetical theory is crucial to the research. It is not even close to being a factual piece of information then how does it contribute as one of the important pillars of research building?

This article will take you through the entire concept of a hypothesis and why it is given so much importance in research.

Understanding the role of hypothesis in research: is it truly as important?

Imagine working on the ideation of research. The very beginning stages of working and planning research. You thought of a research problem that needs a solution.

You see this as something to be worked upon because the solution can help many other researchers in the industry. So now you start finding information on the research problem and if there is any particular document that discusses it already.

All of the information you gathered helped you develop a strong idea that you feel could somehow be connected to or related to the solution to this research problem.

You almost have an intuition, a strong gut feeling that you have discovered the cause of your problem or a solution to it.

Now you wish to analyze and back this intuition of yours with factual data and test scientifically whether or not your intuition is correct or incorrect.

In the process of testing how factual your intuition may be or how real it could be, this intuition becomes your research guide.

This intuitive statement that you are analyzing for facts now is in reality directing your entire research.

Your research is now solely focused on analyzing and testing whether this one angle that you believe intuitively could be the cause or solution is the one that could be the real solution to your research problem. 

This is exactly what Hypothesis is and does. 

So what exactly is a hypothesis?

The hypothesis is a very crucial research tool and as discussed above it plays a very important role in getting started with the research process. But what exactly is a hypothesis? 

Let's decode the word first. In layman’s language “Hypo” stands for hypothetical and “thesis” stands for theory or something that needs to be put to test to determine whether it is true or false, right or wrong.

Put together, it simply means a hypothetical theory or thesis which needs to be put to test to determine whether it is true or false, right or wrong.

As per the Greek words from which the word hypothesis has been derived, hypo means anything that is tentative, or is “subject to verification” (as quoted by many sources) and thesis means “statement about the solution of a problem”.

Put together it gives us the following research definition of the hypothesis.

In Research, a Hypothesis is defined as, a “ Tentative statement about the solution of the problem”. 

The hypothesis is meant to predict what could happen in research at the conclusion. As discussed above a hypothesis is a predictive statement of a tentative solution I.e it does not assure that the same predictive statement will be the conclusion.

It only assumes so for the time being till it tests the possibilities of it being the solution. There's a strong probability that this tentative statement or hypothesis “could be” the solution to the research problem but there is no surety of the same.

It is just a predictive statement that you as a researcher believe could be the driving factor of the research.

For eg: you are working on a research problem I.e why are young adults so frustrated and short-tempered all the time?

After a lot of research on the topic, you come across some research findings that indicate a lack of adequate sleep irritates young adults nowadays or binge-watching web series leads to inadequate sleep which results in agitated young adults throughout the day.

Now, this could be the cause and this could be your conclusion. So you decide that this is the hypothesis of your research and you want to explore this angle in the research. 

Now that we know what a hypothesis is, let's get to know the nature and characteristics of a hypothesis:

1. A hypothesis is always based on concepts: the hypothesis is a predictive statement. It is an assumption about the solution to the research problem. And since you are always formulating a theory or putting the statement to test and verification, you are always dealing with concepts. A hypothesis is based on a simple idea and the basic principles of assumption and prediction that something could be the case. There's not too much technicality involved in the process.

2. A Hypothesis is nothing but a verbal statement in a declarative form: you are trying to declare that this statement could be your solution. This verbal statement is not factual, not something that is already established. 

3. A Hypothesis is based on Empirical Evidence or referents that describe the relationship between two or more variables: when you are working on a hypothesis and trying to prove it, you work on it in a way that each time someone attempts to study this hypothesis they will end up getting the same solution as you did. This is called empirical evidence or referent. A study backed by genuine and accurate methods of analyzing data that will always come to the same conclusion at the end of it. A Hypothesis is also always trying to describe the relationship between two or more variables that are being studied. For eg keeping in mind the frustration among young adults study,  your hypothesis is studying the relationship between the two variables of sleep and its relation with frustration among individuals. If you also consider binge-watching series and sleep and the way they lead to frustration, then you have more than 2 variables being studied. 

4. A hypothesis is always written in the future tense: a hypothesis is always projected as something that will happen in the future. This is because it is only a predictive statement subject to verification. Only in the future upon conducting the research can you surely say that it is a sure-shot solution to your research problem. 

5. A Hypothesis is where your entire research process begins: a hypothesis shapes the direction of the study and guides your research completely in one direction. Without a hypothesis, you will have an infinite number of variables to study and an infinite number of possible solutions to your problem, and all cannot be examined.

What is the importance or significance of the Hypothesis in Research?

• when you have a tentative solution to your research problem it gives your research a direction to focus on and narrow down to. The researcher can now begin somewhere and start analyzing the research by testing the hypothesis.

• The hypothesis sets a basis to conduct research. It gives very specific instructions as to which direction to go in, and which elements should be studied and analyzed. What should be avoided while doing the research? What could be the possible solution? Etc.

• Each Hypothesis can formulate a new one: who said that the one hypothesis you study is your only chance at predicting your solution? You may realize that the one specific factor you are studying has nothing to do with your study but you may have a strong feeling about another factor now. You can simply put an end to studying the first hypothesis and begin working on the new one which you believe has more potential to be the solution. Each hypothesis can lead to the formulation of a new hypothesis.

• A basic rough hypothesis can become your final hypothesis: you may not need to work on a very polished and precise hypothesis. If you have a rough idea of what you wish to study you can start analyzing it and eventually get to the final hypothesis in-depth for your research. It's all about beginning somewhere.

• Once you have a solid hypothesis, you can test and accept or reject it: as a researcher when you are analyzing and testing your hypothesis you can accept it or reject it based on how it suits your research. 

• Hypothesis prevents blind research: no researcher would want to work on goalless and aimless research with no specific direction to explore. Having a hypothesis safeguards your research from being a failed attempt at doing something. 

Let us look at the Types of hypotheses in research methodology:

1. Declarative Statement: This type of Hypothesis is the most commonly used form of a hypothesis. This type of hypothesis provides an anticipated relationship between variables. Be it in the form of prediction, assumption, expectation or forecast, etc. Every hypothesis is a declarative statement hypothesis in essence but with more specificity, the hypothesis may become a different type of hypothesis.

2. Cause & Effect Hypothesis: This hypothesis studies one or more variables that cause an effect on other variables. It studies the cause-and-effect relationship between two or more variables.

3. Directional Hypothesis: Directional Hypothesis has more specificity in it. A Directional Hypothesis sees variables as Independent and Dependent Variables. It believes that an independent variable affects the dependent variable and the direction of the experiment. For eg: example in research study says, 2 grams of caffeine consumption will make you sleep less than 5 hours a night. Here, 2 grams of caffeine is the Independent Variable. It will affect the dependent variable of Sleep and it will also affect the direction of it I.e 5 hours of sleep at night. This is a classic example of a Directional Hypothesis where you can easily see the independent variable's effect on the dependent variable. 

4. Non-Directional Hypothesis: contrary to the Directional Hypothesis is Non-Directional Hypothesis. It is similar to the part where the independent variable will still affect the dependent variable but the only difference here is it will not specify the direction of the effect on the experiment. Using the same experiment of caffeine and sleep research, 2 grams of caffeine will alter how much sleep you will get in hours throughout the night or day. Here caffeine is the independent variable and sleep is the dependent variable but the effect as mentioned in the previous example is not mentioned here I.e the number of hours it will affect the sleep has not been mentioned. This is called Non-directional Hypothesis.

5. Null Hypothesis: As the name suggests this hypothesis believes there is no relationship between the variables involved in a study. this simply means that the variables present in the study have no influence or impact on each other and do not affect the research in any way. An “alternative” to this is that there is a relationship between the two variables and it has a certain influence on the study. This is also known as the Alternative to the Null Hypothesis.

Hypothesis Testing in Data Science:

You've worked very hard on having one or more hypotheses for your research and now you want to test whether this tentative statement is the final solution to your research as well. How do you do that?

The process of hypothesis testing includes certain parameters that help in identifying how close your hypothesis is to bring the actual solution to the research problem at hand.

Since a hypothesis is just a predictive statement it needs to have enough empirical evidence and strong backing by relevant facts to be accepted as a real solution to a problem.

The process of hypothesis testing is done to interpret results and to ensure that the hypothesis is backed with enough factual knowledge to consider it a true solution.

It attempts to collect solid evidence and data that can showcase that the hypothesis is worthy of being the solution.

Hypothesis testing enables the researcher to accept or reject any claim or assumption about the universe or population at large by collecting data from relevant samples with accurate information and data.

Hypothesis testing deals with two types of Hypothesis:

• Null Hypothesis

• Alternative Hypothesis

A null Hypothesis is a statement of no effect and it is very evident. If there is no relationship between two variables to explore the researcher would simply claim that it is a Null Hypothesis and has no effect on the study whatsoever.

An Alternative Hypothesis is a statement that you want to conclude or prove by backing it up with enough data. This type of hypothesis will always have a direct or non-direct effect on the research and the variables involved.

While Testing the Hypothesis, P-Value plays a crucial role. P-Value is the probability Value that helps in accepting or rejecting a Hypothesis.

P-value simply stands for the chances or likelihood of a hypothesis being accepted or rejected by the researcher.

Type 1 and Type 2 Error in Hypothesis Testing:

• Type 1 Error (False Positive): Type 1 is also called a False Positive error. This Error means when the Null Hypothesis is true but you fail to reject it, it is called a false positive. For eg: if an election poll states that a political party will lose the election this year and you reject the news but it comes true and the political party loses the election, it becomes a false positive. 

• Type 2 Error (False Negative): When the Null Hypothesis is False but you fail to reject it, it becomes a false negative. For eg: if the news says that a political party will lose the election and you accept it and fail to reject it and believe that the party will lose, but the party wins the election, this becomes a false negative.

How to Determine Whether a Hypothesis is Good enough?

There are certain parameters to keep in mind. They are:

1. A good Hypothesis always clearly defines assumptions and does not use vague predictive statements.

2. A good hypothesis should be brief and not explain a lot or show any biases or pre-determined judgments.

3. A good hypothesis must have limited assumptions and conditions. Too many assumptions would make the research appear confused and vague with no clarity of thought as to where the research is headed.

4. A good Hypothesis should meet the required criteria. It should fit within the parameters of a testable, verifiable hypothesis. 

5. A good hypothesis should be based on easily verifiable and observable data. There is no point in working on hypothetical statements that cannot be put to test and proved.

6. A good Hypothesis always clearly explains the relationship between two variables and how it affects the research. The relationship between the variables only defines the path or course of the research.

7. The researcher should always work on one hypothesis first and then if needed should come up with a new hypothesis. 

This blog article attempts to highlight the importance of a Hypothesis in Research. A hypothesis is the pivot of all research and it all begins with a proper hypothesis only.

The researcher must ensure that the hypothesis attempts to find the most accurate or closest tentative solution to a problem and should be verifiable and observable.