How many variable are in an experiment

The independent variable is the cause. Its value is independent of other variables in your study. The dependent variable is the effect. Its value d epends on changes in the independent variable.

Examples of independent and dependent variables Research Question Independent variable s Dependent variable s Do tomatoes grow fastest under fluorescent, incandescent, or natural light?

The type of light the tomato plant is grown under The rate of growth of the tomato plant What is the effect of diet and regular soda on blood sugar levels? The type of soda you drink diet or regular Your blood sugar levels How does phone use before bedtime affect sleep?

The amount of phone use before bed Number of hours of sleep Quality of sleep How well do different plant species tolerate salt water? What is your plagiarism score? Compare your paper with over 60 billion web pages and 30 million publications. What are independent and dependent variables? For example, in an experiment about the effect of nutrients on crop growth: The independent variable is the amount of nutrients added to the crop field.

The dependent variable is the biomass of the crops at harvest time. Why are independent and dependent variables important? What is an example of an independent and a dependent variable? The type of soda — diet or regular — is the independent variable.

The level of blood sugar that you measure is the dependent variable — it changes depending on the type of soda. Can a variable be both independent and dependent? The nonmanipulated independent variable was whether participants were high or low in hypochondriasis excessive concern with ordinary bodily symptoms.

The result of this study was that the participants high in hypochondriasis were better than those low in hypochondriasis at recalling the health-related words, but they were no better at recalling the non-health-related words. Such studies are extremely common, and there are several points worth making about them.

First, nonmanipulated independent variables are usually participant variables private body consciousness, hypochondriasis, self-esteem, and so on , and as such they are by definition between-subjects factors. For example, people are either low in hypochondriasis or high in hypochondriasis; they cannot be tested in both of these conditions. Second, such studies are generally considered to be experiments as long as at least one independent variable is manipulated, regardless of how many nonmanipulated independent variables are included.

Third, it is important to remember that causal conclusions can only be drawn about the manipulated independent variable. Thus it is important to be aware of which variables in a study are manipulated and which are not.

The results of factorial experiments with two independent variables can be graphed by representing one independent variable on the x -axis and representing the other by using different kinds of bars or lines. The y -axis is always reserved for the dependent variable. Time of day day vs. It would also be possible to represent cell phone use on the x -axis and time of day as different-coloured bars. The choice comes down to which way seems to communicate the results most clearly.

The bottom panel of Figure 8. This variable, psychotherapy length, is represented along the x -axis, and the other variable psychotherapy type is represented by differently formatted lines. This is a line graph rather than a bar graph because the variable on the x-axis is quantitative with a small number of distinct levels.

Line graphs are also appropriate when representing measurements made over a time interval also referred to as time series information on the x -axis. A main effect is the statistical relationship between one independent variable and a dependent variable—averaging across the levels of the other independent variable. Thus there is one main effect to consider for each independent variable in the study.

The top panel of Figure 8. The blue bars are, on average, higher than the red bars. It also shows a main effect of time of day because driving performance was better during the day than during the night—both when participants were using cell phones and when they were not.

Main effects are independent of each other in the sense that whether or not there is a main effect of one independent variable says nothing about whether or not there is a main effect of the other. The longer the psychotherapy, the better it worked. Although this might seem complicated, you already have an intuitive understanding of interactions. It probably would not surprise you, for example, to hear that the effect of receiving psychotherapy is stronger among people who are highly motivated to change than among people who are not motivated to change.

This is an interaction because the effect of one independent variable whether or not one receives psychotherapy depends on the level of another motivation to change.

If they were high in private body consciousness, then those in the messy room made harsher judgments. If they were low in private body consciousness, then whether the room was clean or messy did not matter.

The effect of one independent variable can depend on the level of the other in several different ways. This is shown in Figure 8. The independent variable is the one that is changed by the scientist.

Why just one? Well, if you changed more than one variable it would be hard to figure out which change is causing what you observe. For example, what if our scientific question was: "How does the size of a dog affect how much food it eats? The data might get a bit confusing— did the larger dog eat less food than the smaller dog because of his size or because it was the middle of the day and dogs prefer to eat more in the morning?

Sometimes it is impossible to just change one variable, and in those cases, scientists rely on more-complicated mathematical analysis and additional experiments to try to figure out what is going on. Older students are invited to read more about that in our Experimental Design for Advanced Science Projects page. To be clear though, for a science fair, it is usually wise to have only one independent variable at a time.

If you are new to doing science projects and want to know the effect of changing multiple variables, do multiple tests where you focus on one independent variable at a time.

The dependent variables are the things that the scientist focuses his or her observations on to see how they respond to the change made to the independent variable.

In our dog example, the dependent variable is how much the dogs eat. This is what we are observing and measuring. It is called the "dependent" variable because we are trying to figure out whether its value depends on the value of the independent variable.

If there is a direct link between the two types of variables independent and dependent then you may be uncovering a cause and effect relationship.

The number of dependent variables in an experiment varies, but there can be more than one. Experiments also have controlled variables.

Controlled variables are quantities that a scientist wants to remain constant, and she or he must observe them as carefully as the dependent variables. For example, in the dog experiment example, you would need to control how hungry the dogs are at the start of the experiment, the type of food you are feeding them, and whether the food was a type that they liked. If you did not, then other explanations could be given for differences you observe in how much they eat. Explore different variables you can expect in your experiments.

As a budding scientist, you want to learn about the world around you. To do that, it is important to explore cause and effect relationships. You even try to predict what will happen through your hypothesis. To test your hypothesis , you need an experiment with a variable. Variables are the factors, traits, and conditions you can modify and measure. But, the most common variables found in a science experiment include dependent, independent , and controlled.

Check out what each is through examples. In an experiment, you need some type of control. Being able to modify a variable is important to study the effects. The variable you control is called your independent variable. Speaking of cause and effect, the independent variable is your cause.