Dependent and Independent Variables

Research has been the backbone of most breakthroughs in our human history with the odd coincidences and mistake discoveries. We have carried out millions of researches to obtain information about different topics.

We cannot advance as a species without it. During the research, we need ways or methods of testing out our theories to confirm our inferences. This is where the term ‘experiment’ comes in. There is no other tool we can use to find out if our assumptions have any basis.

Researchers from various fields of study have utilized the experimental method for centuries to compare and contrast theories with practical knowledge. To understand what variables are, you need to, first of all, know what experimental research is in detail. In this guide, we will discuss the experimental method, what it entails, its types, and the use of variables, both independent and dependent, during research. So, let’s dive right into it.

What is an Experimental Research?

Experimental method/research is a branch of t research that leans towards the more scientific approach. It involves a process whereby one or more independent variables are manipulated and then applied to one or more dependent variables to gauge the effect the former has on the latter.

Usually, experimental research involves the collection of quantitative data and then performing statistical analysis on the data. Mostly related to a lab test procedure, the experimental method has been dubbed as an example of the quantitative research method. This type of research can be conducted during situations like:

  • Invariable behavior between cause and effect
  • Time is an important factor while establishing a connection or relationship between cause and effect
  • The need to understand the role that cause and effect play

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Types of Experimental Research

The types of experimental research design used are primarily determined by the kind of results required, the research subject, and the researcher’s preferences. There are three experimental research designs: pre-experimental, true experimental, and quasi-experimental research.

Pre-Experimental Research

During pre-experimental research, one or more groups are kept under observation for effect, after the potential cause has been factored into the experiment.

This process is used to find out if further investigation is needed for these specific groups. There are three categories under this type of experiment research;

This is a post-test study that involves the consideration of one group

  • One Group Pretest-Posttest

This is when tests are carried out on a group before and after the cause is affected

  • Static-Group Comparison

This is where two or more groups are observed, but only one is administered the cause while the others remain static

True Experimental Research

The true experimental research depends solely on statistical analysis to prove or disprove a thesis. This is the most accurate form of experimental design. It can be carried out with or without a pre-test on two or more randomly selected dependent subjects.

For the most accurate results, true experimental research must have a control group, random distribution, and a variable that can be manipulated by the researcher. There are four different classes of true experimental design, namely;

  • The PostTest Only Control Group

In this class, subjects are randomly placed in control and experimental groups, but only the experimental group is treated before both groups are post-tested

  • The Pretest-Posttest Control Group

For this design, subjects are randomly selected for the control group and experimental group, and both are pretested. Only the experimental group is treated before both groups are then post-tested to observe the new changes.

  • Solomon Four-Group

This design involves randomly assigning subjects to 4 groups, whereby the first two are tested using the posttest method. In contrast, the last two groups are tested with the pretest-posttest method.

Quasi-Experimental Research

The word “quasi” could be interpreted as pseudo, half, or partial. A quasi-experimental research design has some similarities with the true experimental method, but they differ in several ways. Because the quasi-experimental method does not use randomly selected subjects, it is utilized where this is difficult or downright impossible to achieve.

It is largely used by researchers in the educational field, where the administrators are unwilling to consent to the randomized selection of students for experimental samples. Examples of the Quasi-experimental research design includes the counterbalanced design, the time series, and no equivalent control group design.

Uses of Experimental Research

The experimental research method is used in a vast number of situations as it meets a lot of criteria, but here are few examples of where experimental research may be a useful tool;

  • Employee Skill Evaluation

During the employment process, tests are carried out by the organization/company to screen less qualified from the qualified applicants. During this process, employee trading is conducted to improve employee efficiency and productivity, with further tests carried out at the end of each training session to ascertain how effective the training was.

This makes the employees the subject and training, the treatment, all working in a pretest-posttest control group experimental research.

  • For End Of Semester Exams

Specific courses are being taught to students during the semester/term. They are then examined at the end of the semester.

In this case, only one group of meticulously selected subjects are up for consideration. Thus, it is a pre-experimental research method, from a one-shot case study experimental research design.

Characteristics of the Experimental Method

There are three major characteristics of experimental research design, namely;

  • Variable
  • Multi-variable
  • Setting

At this point, you should fully understand what experimental research method is, its types, and uses. As we move forward, you will understand why you needed to know about the experimental research design and its properties.

In the next part of this article, we will only touch on the variable characteristics of the experimental method since that is why you are here. So, let’s discuss firstly what variables are.

Now, Let’s Talk about Variables

During this post, there have been several references to variables bit what are they? In the research process, your inference subject, no matter how abstract or unquantifiable, has to be given an identity. They are referred to as “variables.” A variable in simple terms is a person, place, thing, or phenomenon which you aim to measure in one way or the other.

They are any characteristics that can be referred to using different values, e.g., species, age, height, exam score, etc. In scientific research, researchers’ intention is usually to study the effect of one variable against another. For example, conducting a test to find out if workers in an organization who work for longer hours get higher pay. Here the variable ‘work for longer hours’ is tested against the other variable ‘getting higher pay’, this is referred to as a “cause and effect” relationship study.

The two types of variables used in research are called the independent variable and the dependent variable.

What Are Independent Variables?

The independent variable is the variable that can be quickly and easily manipulated by the administrator. The variable that the experimenter controls or changes is assumed to have a direct effect on the other variable(s).

Two fundamental examples of independent variables are age and time. Why? Because they are abstract entities that cannot be influenced by man or any other force apart from itself. They are independent of external influence, making them the holy grail of independent variables and gender, race, and eye color.

Now, What Are Dependent Variables?

This is the variable that is almost entirely reliant on the influence of other measurable factors. These variables are expected to change as a direct result of the manipulation of the independent variable. It is a presumed effect that originates from the change in nature from the independent variable.

Sometimes referred to as the responding value, it is the variable being studied and measured. Examples of the dependent variable are; your height at different stages in your life and how much you eat in the morning compared to night time. The dependent variables being ‘your height’ and ‘how much you eat.’

Examples of Experiments Utilizing Dependent and Independent Variables

  1. What is the effect of late-night snacks on belly fat?

Independent variable: eating late at night

Dependent variable: Belly fat

  1. What is the effect of regular and diet soda on blood sugar levels?

Independent variable: The type of soda that you consume (soda or diet)

Dependent variable: Your blood sugar levels

  1. How does the use of your phone before bedtime affect the quality of sleep?

Independent variable: How long you use your phone before you go to bed

Dependent variables: Number of hours spent sound asleep

  1. What impact, if any, does x drug have on cancer?

Independent variable: Dosage and timing of drug administration

Dependent variable: Impact of the drug on cancerous cells

  1. Can x vitamin be used to extend someone’s life expectancy?

Independent variable: Amount of vitamins administered to the subject

Dependent variable: Total life span

Graphical Representation Of Dependent And Independent Variables 

The location of independent and dependent variables in a graph chart is relatively constant. This makes discerning the variables much simpler when viewing them through a graph.

The independent variables are placed on the horizontal/x-axis, and the dependent variables are placed on the vertical/x-axis. Below is a graphical representation of an experiment to ascertain the results of the duration of study in comparison with exam scores

independent variables

In this graph, the independent variable, which dubbed as “time studied,” lies on the x-axis against the dependent variable “Score on Exam,” located on the x-axis.

Difference between Dependent and Independent Variables

Although Independent and dependent values have a shared partnership, they are different in a lot of ways, including;

  • Definition

The independent variable is a variable used in statistical modeling, experimental sciences, and mathematical modeling that doesn’t rely on any other variable in the scope of the experiment.

On the other hand, dependent variables are also used in mathematical modeling, statistical modeling, and experimental sciences, but they depend on other variables in the scope of the experiment.

  • Other Names

Other names used to refer to the independent variables are; explanatory variables, controlled variables, and manipulated variables. Dependent variables are referred to as; Responding variables, measured variables, and explained variables.

  • Attributes

Independent variables take the form of experiment stimulus with two either absent or present attributes. Dependent variables attributes are either direct, indirect, or through constructs.

  • Dependence

Just as the name suggests, independent variables are constant variables that do not depend on any other variable from the experiment. While dependent variables are reliant on the nature of the independent variables to function properly in the experiment’s scope.

  • Function

Changes in independent variables directly represent the ’cause’ aspect of the experiment. On the other hand, independent variables’ changes by influence from the independent variables make up the ‘effect’ aspect of the experiment.

  • Existence

Independent variables can stand on their own, meaning they can exist without dependent variables. Dependent variables cannot stand on their own. They need another variable to give them meaning.

  • Executor Of Changes

The experimenter is in charge of making appropriate changes to independent variables’ values, while dependent variables are affected by the nature of changes made to independent variables in an experiment.

  • Graph Values

The independent variable is denoted by ‘x’ on the graph and plotted on the x-axis. In contrast, dependent variables are denoted by ‘y’ on the graph and plotted on the y-axis.

Let’s Introduce Constant Variables

Although Independent variables and dependent variables are the most important variables with regards to experimental research. It is also prompt to note that there are other types of variables, including constant variables.

Constant variables can be simply defined as the constant values during the entire process of the experiment. For example, in Experiment 1 above, the constant variables will be; Bedtime, snack consumed, time of the meal, etc.

Wrapping It up

By now, you should know all there is to know about variables, independent and dependent, their similarities, functions, and differences.

The experimental research design is a vast subject that spreads further into different topics depending on the study’s scope. So, you can do further research on specific fields of study.

Also, note that the other names of these variables are only referred to in special circumstances, so to avoid confusion, always stick to their original names.

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