--In Example 1 (stretching an elastic band) it shows the weight (independent variable) changing the elastic’s length (dependent variable). But you could just as easily say that you were changing the length of the elastic (independent) and then measuring how much weight was needed (dependent).
--The simplest rule is to emphasise that the variable that YOU change is the independent (or input) variable.
--Many students would find it easier to use the terms ‘input’ variable and ‘outcome’ variable, as these are more descriptive …but the UK exam specifications (and exam papers) do not use these terms.
--In Example 3 (current in a circuit) the voltage is increased by adding more cells. You could say that the number of cells is the independent variable (assumes that the cells are identical).
This would be an example of a discrete variable.
Simplified example
The independent variable is typically the variable being manipulated or changed and the dependent variable is the observed result of the independent variable being manipulated. For example concerning nutrition, the independent variable of your daily vitamin C intake (how much should I take) can determine the dependent variable of your life span (what is the result or observation as a result of manipulating the 'independent variable'). Scientists will manipulate the vitamin C intake in a group of lets say 100 people who are over the age of 65. Half of the group, 50 people will be given a daily high dose of vitamin C (lets say 2000 mg) and 50 people will be given a placebo pill (no vitamin C dose or a pill with zero vitamin C) over a period of 25 years. The scientists will log the life span of the 100 people to see if there is any statistically significant change in the life span of the people who took the high dose and those who took the placebo (no dose). The goal is to see if the independent variable of high vitamin C dosage affects the dependent variable of people's life span.
Alternative terminology in statistics
In statistics, the dependent/independent variable terminology is used more widely than just in relation to controlled experiments. For example the data analysis of two jointly varying quantities may involve treating each in turn as the dependent variable and the other as the independent variable. However, for general usage, the pair response variable and explanatory variable is preferable as quantities treated as "independent variables" are rarely statistically independent.[3][4]
Depending on the context, an independent variable is also known as a "predictor variable," "regressor," "controlled variable," "manipulated variable," "explanatory variable," "exposure variable," and/or "input variable."[5] A dependent variable is also known as a "response variable," "regressand," "measured variable," "observed variable," "responding variable," "explained variable," "outcome variable," "experimental variable," and/or "output variable."[6]
In addition, some special types of statistical analysis use terminology more relevant to the specific context. For example reliability theory uses the term exposure variable for what would otherewise be an explanatory or dependent variable, and medical statistics may use the term risk factor.
Examples
If one were to measure the influence of different quantities of fertilizer on plant growth, the independent variable would be the amount of fertilizer used (the changing factor of the experiment). The dependent variables would be the growth in height and/or mass of the plant (the factors that are influenced in the experiment) and the controlled variables would be the type of plant, the type of fertilizer, the amount of sunlight the plant gets, the size of the pots, etc. (the factors that would otherwise influence the dependent variable if they were not controlled).[citation needed]
In a study of how different doses of a drug affect the severity of symptoms, a researcher could compare the frequency and intensity of symptoms (the dependent variables) when different doses (the independent variable) are administered, and attempt to draw a conclusion.[citation needed]
In measuring the acceleration of a vehicle, time is usually the independent variable, while speed is the dependent variable. This is because when taking measurements, times are usually predetermined, and the resulting speed of the vehicle is recorded at those times. As far as the experiment is concerned, the speed is dependent on the time. Since the decision is made to measure the speed at certain times, time is the independent variable.[citation needed]
In measuring the amount of color removed from beetroot samples at different temperatures, the dependent variable would be the amount of pigment removed, since it is depending on the temperature (which is the independent variable).[citation needed]
In sociology, in measuring the effect of education on income or wealth, the dependent variable could be a level of income or wealth measured