1. What is Variables ?

How do I design an experiment?

When designing an experiment, you should:

Determine the question you are trying to answer.

List your independent and dependent variables, plus any controlled, confounding or additional variables.

Write a hypothesis that you believe your experiment will prove.

Decide how much you want to manipulate your independent variable.

Determine the number of samples or subjects in your study.

Assign subjects into treatment groups.

1. What is Variables ?

How do you control confounding variables?

Ways to control confounding variables so they do not affect the results of your experiment include:

Adjustment: Adjust study parameters to account for the confounding variable and minimize its effects.

Matching: Compare study groups with the same degree of confounding variables.

Multivariate analysis: Use when analyzing multiple variables at once.

Randomization: Spread confounding variables evenly between study groups.

Restriction: Remove subjects or samples that have confounding factors.

Stratification: Create study subgroups in which the confounding variable does not vary or vary much.

1. What is Variables ?

How many variables are in an experiment?

Every experiment has at least two variables—an independent variable and a dependent variable. The independent variable is what you are testing, and the dependent variable is the result. Any other variables in your experiment build on or affect the independent or dependent variables. Most experiments also include a controlled variable.

1. What is Variables ?

What is a variable?

A variable is any characteristics, number, or quantity that can be measured or counted. A variable may also be called a data item. Age, sex, business income and expenses, country of birth, capital expenditure, class grades, eye colour and vehicle type are examples of variables. It is called a variable because the value may vary between data units in a population, and may change in value over time.

For example; ‘income’ is a variable that can vary between data units in a population (i.e. the people or businesses being studied may not have the same incomes) and can also vary over time for each data unit (i.e. income can go up or down).