What type of hypothesis states the relationship between independent and dependent variables?

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The research hypothesis states that there is an association or difference

With hypothesis testing, the research hypothesis states that there IS a difference or association between variables of interest. Researchers have conducted a literature review and created a valid and credible research question. Now, they can make an informed and evidence-based research hypothesis that there will be a difference/association/effect.When statistical significance is achieved in the context of hypothesis testing, then researchers "reject" the null hypothesis. This means that researchers have found a significant difference/association/effect, and can therefore reject the idea that there is NO difference/association/effect.When conducting research, this is the researchers' hypothesis. They are unsure if a treatment or a characteristic or a predictor/independent variable has an association with an outcome/dependent variable, but they believe it does. They are conducting the research study to see if it does or does not exist. The research hypothesis is the reason for conducting research. There is a research question that needs to be answered, and researchers believe that what they want to do or study is an answer to that question!

Remember that human beings bring presuppositions and biases into everything they do. This is especially true in applied research and hypothesis testing. It just feels GOOD to find the outcomes/differences/associations that researchers believe exist. And researchers will cut corners and manipulate their data analyses in order to find truth in their hypotheses. This is a good reason for the focus of hypothesis testing being strictly on the null hypothesis. When statistical significance is not achieved when testing the primary hypothesis (p > .05), then it is the null hypothesis that researchers "do not reject," rather than the research hypothesis. 

Research hypothesis and between-subjects research design

The research hypothesis is stated in different fashions according to the number of groups being compared in between-subjects research designs.

For between-subjects designs with one group, the research hypothesis states that there is a significant difference between the expected proportion (categorical outcome), median (ordinal outcome), or mean (continuous outcome) and the observed proportion, median, or mean.

For between-subjects designs with two groups, the research hypothesis states that there is a significant difference between the proportions (categorical outcome), medians (ordinal outcome), or means (continuous outcome) of the two groups.

For between-subjects designs with three or more  groups, the research hypothesis states that there is a significant difference between the proportions (categorical outcome), medians (ordinal outcome), or means (continuous outcome) of the three or more  groups. 

Research hypothesis and within-subjects research design

For within-subjects research designs, the research hypothesis is stated in a fashion that reflects the number of observations of an outcome that are being analyzed.

For within-subjects designs with two groups, the research hypothesis states that there is a significant difference between the "pre" and "post" observations of proportions (categorical outcome), medians (ordinal outcome), or means (continuous outcome).

For within-subjects designs with three groups, the research hypothesis states that there is a significant difference between the "pre," "post," and "maintenance" observations of proportions (categorical outcome), medians (ordinal outcome), or means (continuous outcome). 

Research hypothesis and correlation design

When writing the research hypothesis for a correlation design, it states that there is a significant association between the two variables that are being correlated. The expected correlation for the research hypothesis is not equal to zero, "0."

Research hypothesis and multivariate design

The research hypothesis for a multivariate design using some form of regression is that the slope is not equal to zero, "0." If there is a significant relationship between variables in a regression model, the slope will not equal zero.

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To conduct a perfect survey, you should know the basics of good research. That’s why in Startquestion we would like to share with you our knowledge about basic terms connected to online surveys and feedback gathering. Knowing the basis you can create surveys and conduct research in more effective ways and thanks to this get meaningful feedback from your customers, employees, and users. That’s enough for the introduction – let’s get to work. This time we will tell you about the hypothesis.

What is a Hypothesis?

A Hypothesis can be described as a theoretical statement built upon some evidence so that it can be tested as if it is true or false. In other words, a hypothesis is a speculation or an idea, based on insufficient evidence that allows it further analysis and experimentation.  

The purpose of a hypothetical statement is to work like a prediction based on studied research and to provide some estimated results before it ha happens in a real position. There can be more than one hypothesis statement involved in a research study, where you need to question and explore different aspects of a proposed research topic. Before putting your research into directional vs non-directional hypotheses, let’s have some basic knowledge.

Most often, a hypothesis describes a relation between two or more variables. It includes:

An Independent variable – One that is controlled by the researcher

Dependent Variable – The variable that the researcher observes in association with the Independent variable.

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How to write an effective Hypothesis?

To write an effective hypothesis follow these essential steps.

The very first step in writing an effective hypothesis is raising a question. Outline the research question very carefully keeping your research purpose in mind. Build it in a precise and targeted way. Here you must be clear about the research question vs hypothesis. A research question is the very beginning point of writing an effective hypothesis.

Do Literature Review

Once you are done with constructing your research question, you can start the literature review. A literature review is a collection of preliminary research studies done on the same or relevant topics. There is a diversified range of literature reviews. The most common ones are academic journals but it is not confined to that. It can be anything including your research, data collection, and observation.

At this point, you can build a conceptual framework. It can be defined as a visual representation of the estimated relationship between two variables subjected to research.

Frame an Answer

After a collection of literature reviews, you can find ways how to answer the question. Expect this stage as a point where you will be able to make a stand upon what you believe might have the exact outcome of your research. You must formulate this answer statement clearly and concisely.

Build a Hypothesis

At this point, you can firmly build your hypothesis. By now, you knew the answer to your question so make a hypothesis that includes:

• Applicable Variables                     
• Particular Group being Studied (Who/What)
• Probable Outcome of the Experiment

Remember, your hypothesis is a calculated assumption, it has to be constructed as a sentence, not a question. This is where research question vs hypothesis starts making sense.

Refine a Hypothesis

Make necessary amendments to the constructed hypothesis keeping in mind that it has to be targeted and provable. Moreover, you might encounter certain circumstances where you will be studying the difference between one or more groups. It can be correlational research. In such instances, you must have to testify the relationships that you believe you will find in the subject variables and through this research.

Build Null Hypothesis

Certain research studies require some statistical investigation to perform a data collection. Whenever applying any scientific method to construct a hypothesis, you must have adequate knowledge of the Null Hypothesis and an Alternative hypothesis.

Null Hypothesis: 

A null Hypothesis denotes that there is no statistical relationship between the subject variables. It is applicable for a single group of variables or two groups of variables. A Null Hypothesis is denoted as an H0. This is the type of hypothesis that the researcher tries to invalidate. Some of the examples of null hypotheses are:

–        Hyperactivity is not associated with eating sugar.

–        All roses have an equal amount of petals.

–        A person’s preference for a dress is not linked to its color.

Alternative Hypothesis: 

An alternative hypothesis is a statement that is simply inverse or opposite of the null hypothesis and denoted as H1. Simply saying, it is an alternative statement for the null hypothesis. The same examples will go this way as an alternative hypothesis:

–        Hyperactivity is associated with eating sugar.

–        All roses do not have an equal amount of petals.

–        A person’s preference for a dress is linked to its color.

Types of Hypothesis

Apart from null and alternative hypotheses, research hypotheses can be categorized into different types. Let’s have a look at them:

Simple Hypothesis:

This type of hypothesis is used to state a relationship between a particular independent variable and only a dependent variable.

Complex Hypothesis:

A statement that states the relationship between two or more independent variables and two or more dependent variables, is termed a complex hypothesis.

Associative and Causal Hypothesis:

This type of hypothesis involves predicting that there is a point of interdependency between two variables. It says that any kind of change in one variable will cause a change in the other one.  Similarly, a casual hypothesis says that a change in the dependent variable is due to some variations in the independent variable.

Directional vs non-directional hypothesis

Directional Hypothesis:

A hypothesis that is built upon a certain directional relationship between two variables and constructed upon an already existing theory, is called a directional hypothesis. To understand more about what is directional hypothesis here is an example, Girls perform better than boys (‘better than’ shows the direction predicted)

Non-directional Hypothesis:

It involves an open-ended non-directional hypothesis that predicts that the independent variable will influence the dependent variable; however, the nature or direction of a relationship between two subject variables is not defined or clear.

For Example, there will be a difference in the performance of girls & boys (Not defining what kind of difference)

As a professional, we suggest you apply a non-directional alternative hypothesis when you are not sure of the direction of the relationship. Maybe you’re observing potential gender differences on some psychological test, but you don’t know whether men or women would have the higher ratio. Normally, this would say that you are lacking practical knowledge about the proposed variables. A directional test should be more common for tests.