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Statistics 101: Principles of Statistics8 chapters | 64 video lessons

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Instructor:
*Nadine James*

Nadine has taught nursing for 12 years and has a PhD in Nursing research

In this lesson, you will learn the definition of variables in science. In addition, you will be able to define the specific types of variables in an experiment.

We also recommend watching Random Variables: Definition, Types & Examples and Continuous, Discrete & Categorical Variables: Definition and Examples

A **variable ** is any item, factor, or condition that can be controlled or changed. There are three types of variables in scientific experiments, but we will define them later in the lesson. First, let's discuss why scientists use experiments. An experiment is used to determine an association between different variables looking for a cause and effect relationship. A cause and effect relationship means that when you alter one or more variable(s), and measure or observe another variable while keeping everything else the same, there is an effect on the variable that you can measure or observe. This type of experiment is very important because, if there is a cause and effect relationship between variables, then outcomes are predictable and can be used to an advantage or may be manipulated or changed. More on why this is important a little later in the lesson.

Now let's talk about those three types of variables used in scientific experiments. The first variable type is called the **independent variable**. This variable is the one that is manipulated or changed by the scientist. A second type of variable is the one that is observed or measured in the experiment, and it is known as the **dependent variable**. You can remember this because the observation or measure of this variable will change as the independent variable is altered.

Let's use an example that may assist you to understand these two types of variables. You have a plastic container with water inside. You place the container in a metal box and raise the temperature. Here the temperature is the independent variable (remember you are adjusting the temperature) so you are changing the variable. The water is the dependent variable. If there is a cause and effect relationship between water and temperature, then the water will change with the temperature change. And of course, we know that the water will change from liquid into gas/steam with rising temperatures in the box.

But what about that third type of variable used in scientific experiments? It is the **control variable**, also known as the **constant variable**. As the name suggests, it is the variable that the scientist wants to remain the same. Often, there is more than one control/constant variable in a scientific experiment. The scientist will want to observe these control variables as much as the dependent variable. But why is this important? The reason is that if the control variable(s) is/are not held constant, the scientist will not know if the independent variable caused the change in the dependent variable or if the change was due to the control variable.

In our example above, what would be the control variable? The answer is air pressure. The same conditions must exist if we are to be able to predict the change in the water at a certain temperature. At high-level atmospheres, water boils or turns to steam at a lower temperature level then at normal air conditions.

Below is a line graph that shows where the data points would be shown for the dependent and independent variables in a study. Notice that the control variable is not represented in the line graph. The y axis represents the dependent variable and the x axis is the independent variable. In our example, the dependent variable water would be plotted on the y-axis and the independent variable - temperature would be plotted on the X-axis.

Remember earlier in the lesson the point was made that if a cause and effect relationship was found in a scientific study then the outcomes can be manipulated or changed? Let's discuss that point briefly now. In our example of water, turning to steam at a certain temperature what can be useful in this example. Once we hold the air pressure constant at sea level than we know if we need steam we need to adjust (or manipulate) the temperature to 212 degrees F to produce steam. This of course is a very simple example just to illustrate the point of the cause and effect relationship. Another lesson to address the complexities of the cause and effect relationship between variables in scientific studies can be taken later in your studies.

In this lesson, you learned the definition of variables in science and the importance of the variables in relation to scientific experiments. After taking this lesson, you should be able to define the specific types of variables and understand the relationship of variables in an experiment. Finally, after doing the lesson and seeing the example provided you should be able to apply a variables relationship and importance of that relationship to the experiment in a real scientific experiment.

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Statistics 101: Principles of Statistics8 chapters | 64 video lessons

- Go to Probability

- Random Variables: Definition, Types & Examples 9:53
- Developing Discrete Probability Distributions Empirically & Finding Expected Values 10:09
- Dice: Finding Expected Values of Games of Chance 13:36
- Blackjack: Finding Expected Values of Games of Chance with Cards 8:41
- Go to Discrete Probability Distributions

- Go to Sampling

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