What condition is needed for an experiment to have useful data

An independent variable is the potential stimulus or cause, usually directly manipulated by the experimenter, so it could also be called a manipulative variable.

A dependent variable is the response or measure of results.

Extraneous variables — other than the independent variable — potentially can affect the dependent variable, so they must be controlled. If possible, you try to keep them constant between the experimental and control group.

The experimental group receives the independent variable.

The control group is similar to experimental, except it does not receive the independent variable. Extraneous variables are balanced between experimental and control groups.

Types of experiments

1. Single blind gives the control group a placebo — a substance that is inert, it has no physical effect. Subjects don't know if they are in experimental or control group to reduce placebo effect, a change in behavior solely due to believing that you are getting the independent variable.

2. Double blind keeps both subjects and experimenter ignorant of group setup. Distribution of the independent variable and placebo are controlled by third party. This controls for experimenter bias and self-fulfilling prophecy, which means that experimenters with particular expectations are likely to consciously or unconsciously to bias the experiment and influence it to conform to their expectations.

As an example, suppose you want to find out if fluorides reduce dental cavities. You would find two groups, trying to control the extraneous variables. Extraneous variables are found by surveying previous research in the area. In this case, you would match the groups in terms of previous history of cavities, diet and dental hygiene habits including how and how often they brush their teeth.

The experimental group would get toothpaste with the independent variable, the fluoride, while the control group would not have the fluoride in their toothpaste. The toothpaste without the fluoride would be the placebo.

The dependent variable would be the number of cavities after participating in the experiment for a time. The dependent variable indicates the results, but it is not the results. At the end of the experiment, both groups could have no change in cavities or one of the groups could have a greater reduction in cavities. (Of course, if the fluoride increased cavities, you wouldn't want to use it.) All of these varied results would be indicated in terms of the dependent variable.

If only the subjects do not know who is getting the fluoride, it is a single blind experiment. If both the subjects and experimenter do not know, it is a double blind.

For an experiment to have useful data, it is crucial to ensure certain conditions are met:

1. Controlled Variables: It is important to control or eliminate any factors other than the independent variable that could influence the results. By keeping all other variables constant, you can establish a cause-and-effect relationship between the independent variable and the outcome.

2. Randomization: Random allocation of participants or samples to different groups is essential to ensure that any observed differences are due to the experimental manipulation rather than pre-existing characteristics. Randomization helps in minimizing bias and ensures that the groups are comparable.

3. Sample Size: Having an adequate sample size is necessary to obtain reliable and meaningful results. A small sample size may lead to false conclusions or limited generalizability. Statistical techniques can be used to determine the appropriate sample size based on the desired effect size, power, and significance level.

4. Avoiding Bias: Bias can occur when there are systematic errors in the design or conduct of the experiment. Common biases include selection bias, measurement bias, and publication bias. Minimizing bias involves careful design, blinding procedures, and using objective measures of outcomes.

5. Replication: Replicating an experiment involves repeating it with different participants or samples. Replication helps establish the consistency and reliability of the findings. It provides confidence that the results are not due to chance or specific characteristics of the sample.

6. Clear and Measurable Outcomes: Clearly defining the outcome variables and using reliable and valid measures is essential. Well-defined outcomes ensure that the data collected is meaningful and allows for proper interpretation and analysis.

By ensuring these conditions are met, an experiment is more likely to generate useful data that can provide reliable insights and contribute to scientific knowledge.