The Difference between Correlation and Causation
Correlation vs. Causation: Key Differences Explained SHARE THE ARTICLE ON Table of Contents When we look at data and research, it’s important to know the
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As we looked at the overview of the experimental design, here 5 major components of the experimental design that we have to pay attention to while conducting our research through experimental design approach:
We have heard this word many times. Observation is basically the first step towards any scientific research. It is a way for gathering data through observing the subjects. The researcher has to go to the participants’ environment and observe the way they behave, react and respond to the natural phenomenon.
Structured observations are conducted with respect to pre-defined variables and schedule, whereas unstructured observations are conducted in a free manner with no pre-defined variables and schedule.
Observational approach allows you to have a direct access to the phenomena and helps you have a long term record regarding the same. That being said, there is a high chance that the observation will be influenced by the biases of the observer. Or in other sense, the presence of an observer himself might change the behaviour of the subjects.
Example: to study the above topic, the researcher will observe the kids who play violent video games on regular basis to study their behaviour and if they show any signs of aggression or impatience.
Questions are the important way to gather primary data. Researcher asks questions to the participants about particular topics or points that he wants to cover while studying the research problem.
Questions can be asked through surveys – which are sent to the participants through various online and offline channels, interviews – where the researcher himself asks questions to the participants on one-on-one basis.
There are two main types of questions asked to the participants:
For example: On a scale of 1-5, how much did you like our event?
For example: Can you tell us how to improve?
When a researcher picks up a topic to research, he formulates a hypothesis. A hypothesis is nothing but an assumption statement that defines the cause-effect relationship between two or more variables. This statement can be proved true or false, depending on the result of the research.
A researcher will put forth this hypothesis regarding his research topic and will begin to conduct the research. The prime benefit of formulating a hypothesis is, it sets out a guideline for how the research is to be conducted and within what bounds. Hence, the researcher will gather the information that is enough to prove the hypothesis true or false.
For the same reason, it is important to know how to write a hypothesis that appropriately covers all the concepts in your research topic. Apart from that, there is a fair chance that the researcher’s bias will interfere with the study. This happens when the researcher is personally in favour of a hypothesis being either true or false.
Example: For the above research topic, its formulated hypothesis can be “Overuse of violent video games affects the behaviour of new generation.”
Explore all the survey question types possible on Voxco
Explore all the survey question types possible on Voxco
Once the hypothesis is ready, the next challenge for the researcher is to choose a proper research design method to run the entire study through. This will depend on how he wants his research to be conducted. Whether the research wants his sample to be assigned randomly, or not, whether there are any control variables, matters a lot while selecting an approach for the research.
Depending on their use, there are three main experimental design types:
As the name suggests, pre-experimental design is carried out before a true experiment is conducted. In this, one or more groups are kept under observation after giving them a treatment related to the research study. Depending on the number of groups involved and the performed pre-test post-test techniques, pre-experimental design is further classified into three: Static group comparison, one group pretest-postest design and one-shot case study.
This is the perfect form of experimental design whose purpose is to test the hypothesis and prove it true or false. It is the most commonly used method of experimental design and its characteristics include random sample assignment, presence of a control group against a treatment group, variable manipulation.
This method is similar to the true experimental design. Except it doesn’t have randomization of the sample. It has a treatment and control group which the researcher observes to derive the causal relationship between the variables.
The final component that defines an experimental design is, of course, the results. After the observations, surveys and interviews and running the research process through any one of the above-mentioned types of research design, the researcher will have the result of the hypothesis testing.
This result will be either for or against the hypothesis.
Example: In our example, the researcher observes the behaviour of the children who has a habit of playing violent video games excessively, and he then conducts a survey or interview with their parents regarding their in general behaviour in the family and friends. On conducting the needed research, he found out that the hypothesis that he framed was true.
Conclusion: The hypothesis “Overuse of violent video games affects the behaviour of new generation” is true.
Researchers carry out an experiment to research a certain decision or result. In order to achieve that, they take their study through various phases of an experimental design right from observation to treating experimental groups and data analysis. While doing so, various things affect the credibility of the conducted research and make the researcher questions the results.
We are here to help you with some of the components that will ensure the validity of your experiment and its results:
As we know, there are two groups in an experiment namely the treatment group and the control group. A control group is a group that does not receive any treatment concerning the research. This group is then compared to the treatment group which went through the experiment. The results will show how whether the experiment is a fail or a success.
Example: the treatment group is of people who have a weak vocabulary and are made to read books, while the control group were never made to do so. When the experiment ended, the results show that the treatment group did way better in the post-test than in the pre-tests while the control group were on the same level.
It is a variable in a hypothesis that affect a dependent variable. This variable is controlled and manipulated by the researcher to see its effect on the experiment. In our example, the independent variable would be the number of books the treatment group was made to read. And to see if the number of books will affect the vocabulary in a significant way.
This is a variable that is dependent on the independent variable. As the researcher manipulated the independent variable, and if its result is significant, then it is bound to make the respective changes in the dependent variable as well. In our example, the dependent variable would be the level of the vocabulary of the treatment group and how it differs depending on the manipulation of the independent variable.
While experimenting, there might be some external variables that influence the dependent variable to change other than the independent variable. In our example, it can be gender, age, grasping ability, etc. Holding these variables constant across the research will minimize the effects they have on the dependent variables.
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The components of experimental design are control, independent variable and dependent variable, constant variables, random assignment and manipulation. These are the components that also help you define if the experiment is valid.
The 5 steps of designing an experiment are literature history, observation, hypothesis, experiment methodology and conclusion. The researcher follows these steps to get the conclusions regarding the research study.
The experiments are meant to be defect and bias-free when their results come out. Hence the components that ensure these things are control, independent variables, dependent variables and constant variables.
The experimental questions are supposed to be short, clear, concise, and focused on the purpose of the research study. These questions will be the footing for the entire research process and are treated as guidelines for the same.
A good and well-conducted experiment design always has these components that define them: Observation, questions, hypothesis formulation, methodology, results. The researcher has to look for any interventions or biases in any of those phases to ensure a defect-free result.
The four basic principles of experimental design are:
Block – block the external variables that might affect the results of the experiment like age, gender, genetics, etc.
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