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Research Methodology

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❶Be practicable — can you measure the variables in question?

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What Is a Hypothesis?

These variables are often stated in experimental research , in a hypothesis , e. In explorative research methodology, e. They might not be stated because the researcher does not have a clear idea yet on what is really going on. Confounding variables are variables with a significant effect on the dependent variable that the researcher failed to control or eliminate - sometimes because the researcher is not aware of the effect of the confounding variable. The key is to identify possible confounding variables and somehow try to eliminate or control them.

Operationalization is to take a fuzzy concept conceptual variables , such as ' helping behavior ', and try to measure it by specific observations, e. The selection of the research method is crucial for what conclusions you can make about a phenomenon.

It affects what you can say about the cause and factors influencing the phenomenon. It is also important to choose a research method which is within the limits of what the researcher can do. Time, money, feasibility, ethics and availability to measure the phenomenon correctly are examples of issues constraining the research.

Choosing the scientific measurements are also crucial for getting the correct conclusion. Some measurements might not reflect the real world, because they do not measure the phenomenon as it should. To test a hypothesis , quantitative research uses significance tests to determine which hypothesis is right. The significance test can show whether the null hypothesis is more likely correct than the research hypothesis.

Research methodology in a number of areas like social sciences depends heavily on significance tests. A significance test may even drive the research process in a whole new direction, based on the findings. The t-test also called the Student's T-Test is one of many statistical significance tests, which compares two supposedly equal sets of data to see if they really are alike or not. The t-test helps the researcher conclude whether a hypothesis is supported or not. Drawing a conclusion is based on several factors of the research process, not just because the researcher got the expected result.

It has to be based on the validity and reliability of the measurement, how good the measurement was to reflect the real world and what more could have affected the results. Anyone should be able to check the observation and logic, to see if they also reach the same conclusions. Errors of the observations may stem from measurement-problems, misinterpretations, unlikely random events etc. A common error is to think that correlation implies a causal relationship.

This is not necessarily true. Generalization is to which extent the research and the conclusions of the research apply to the real world. It is not always so that good research will reflect the real world, since we can only measure a small portion of the population at a time. Validity refers to what degree the research reflects the given research problem, while Reliability refers to how consistent a set of measurements are. Developing testable research hypotheses takes skill, however, along with careful attention to how the proposed research method treats the development and testing of hypotheses.

Before jumping into writing research hypotheses it is crucial to first consider the general research question posed in a study. This seemingly obvious aspect of research can be deceptively difficult to pin down, as researchers often have an unstated sense of what they want to achieve in a study and excitement about doing so that makes it challenging to clearly state a research question. Glenn Firebaugh identified two key criteria for research questions: Researchable implies that a question can be answered through empirical research that is, something that science can address and also limited enough that a study could actually hope to answer the question in a reasonable period of time.

The requirement that the research question be interesting implies primarily that the question be important in the context of the ongoing scientific discussion of the topic that is, interesting to other researchers. Hypotheses in Quantitative Studies Research hypotheses in quantitative studies take a familiar form: Generally the independent variable is mentioned first followed by language implying causality terms such as explains, results in and then the dependent variable; the ordering of the variables should be consistent across all hypotheses in a study so that the reader is not confused about the proposed causal ordering.

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Hypothesis. In research, a hypothesis is a suggested explanation of a phenomenon. A null hypothesis is a hypothesis which a researcher tries to disprove. Normally, the null hypothesis represents the current view/explanation of an aspect of the world that the researcher wants to challenge.

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An hypothesis is a specific statement of prediction. It describes in concrete (rather than theoretical) terms what you expect will happen in your study. Not all studies have hypotheses. Sometimes a study is designed to be exploratory (see inductive research). There is no formal hypothesis, and perhaps the purpose of the study is to explore some area more thoroughly in order to develop some specific .

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The research hypothesis is a paring down of the problem into something testable and falsifiable. In the above example, a researcher might speculate that the decline in . Put simply, a hypothesis is a specific, testable prediction. More specifically, it describes in concrete terms what you expect will happen in a certain circumstance. A hypothesis is used to determine the relationship between two variables, which are the two things that are being tested.

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Characteristics of hypothesis in Research Methodology Characteristics of hypothesis: Hypothesis must possess the following characteristics: Hypothesis should be clear and precise. This type of research method might be used to investigate a hypothesis that is difficult to test experimentally. Experimental Research Methods Experimental methods are used to demonstrate causal relationships between variables.