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Experimentation or experimental research is one in which independent variables are manipulated to determine their effect on the dependent variable. The main objective of experimental research is to access the cause and effect relationship among variables. Suppose, we want to test whether a training program has an influence on employee skills. Here, the training program is the independent variable & employee skill is the dependent variable. Now, we take a sample of 50 employees; who are divided into two groups.

Each group consists of 25 employees. We can denote the two groups as group A & group B. Now, all the employees of group A are given training & no training is given to group B employees.

At the weekend, we measure the skill of the employees through their productivity (e.g. the number of units they produce). Now, if the productivity of group A employees is higher than that of group B, then we can say that the training program has a significant effect on employee skills.

This is an example of experimentation. Here, the independent variable (training program) is manipulated to determine its effect on the dependent variable (skill of the employee).

Experiments are widely used in causal research. The researcher’s goal in conducting an experiment is to determine whether changing the experimental independent variable causes changes in the specified dependent variable.

Important Concepts of What is Experimental Research Design

Dependent and independent variables: A concept that might battle completely different quantitative values is named a variable. per se the ideas like weight, height, financial gain are all samples of variables.

Qualitative phenomena (or the attributes) are also qualified on the basis of the presence or absence of the concerning attribute(s). Phenomena that might attack quantitatively totally different values even in decimal points are referred to as ‘continuous variables’. But all variables are not continuous.

Extraneous variable:

Independent variables that don’t seem to be associated with the aim of the study, however, might have an effect on the variable quantity area unit termed as extraneous variables.

Suppose the researcher wants to test the hypothesis that there is a relationship between children’s gain in social studies achievement and their self-concepts. In this case, self-concept may be an experimental variable and social studies accomplishment is a variable.

Control:

One important characteristic of good research design is to minimize the influence or effect of extraneous variable (s). The technical term ‘control’ is employed once we style the study minimizing the results of extraneous freelance variables. In experimental researches, the term ‘control’ is employed to discuss restraining experimental conditions.

Confounded relationship:

When the dependent variable is not free from the influence of extraneous variables(s), the relationship between the dependent and independent variables is said to be confounded by an extraneous variable(s).

Research hypothesis:

When prediction or a hypothesized relationship is to be tested by scientific methods if termed as a research hypothesis. The analysis hypothesis may be a prophetical statement that relates an associate variable to a variable quantity.

Experimental and non-experimental hypothesis testing research:

When the aim of the analysis is to check a research hypothesis, it’s termed hypothesis-testing analysis. It is often of the experimental style or of the non-experimental style.

Research in which the independent variable is manipulated is termed ‘experimental hypothesis-testing research’ and research in which an independent variable is not manipulated is called ‘non-experimental hypothesis-testing research’.

Experimental and control groups:

In experimental hypothesis-testing research when a group is exposed to usual conditions it is termed a ‘control group’ but when the group is exposed to some novel or special condition, it is termed an experimental group.

Treatments:

The different conditions under which experimental and control groups are put are usually referred to as ‘treatments’. In the illustration taken higher than, the 2 treatments area unit the same old studies program. Similarly, if we would like to work out through AN experiment the comparative impact of 3 kinds of fertilizers on the yield of wheat, in this case, the 3 kinds of fertilizers are treated as 3 treatments.

Experiment:

The process of examining the truth of a statistical hypothesis, relation to some research problem, is known as an experiment. For example, we can conduct an experiment to examine the usefulness of a certain newly developed drug.

Experiments can be of two types such as absolute experiment and comparative experiment. If we want to determine the impact of fertilizer on the yield of croup, it is a case of the absolute experiment.

But if we want to determine the impact of one fertilizer as compared to the impact of some other fertilizer, our experiment then will be termed as a comparative experiment. Often, we undertake comparative experiments when we talk of the design of experiments.

Experimental units:

The pre-determined plots or the blocks, when different treatments are used, are known as experimental units. Such experimental units must be selected (defined) very carefully.