Dependent and Independent Variables 640 336 Visual Veggies

Dependent and Independent Variables

Dependent and Independent Variables

A variable is something a researcher is trying to measure, and it can be just about anything, including objects, amounts of time, feelings, or events.  Researchers in the field of nutrition might measure variables such as lab values, weights, effects of a medication, athletic performance, and so on.


There are two key variables in every experiment:

The independent variable is what the researcher changes or the variable that changes on its own, such as age or time.  The independent variable may also be referred to as the “manipulated variable”.  This variable is not affected by any other variable in the experiment.

The dependent variable is the variable being studied or measured.  This may also be referred to as the “responding variable”.  The dependent variable changes as a result of the changes made to the independent variable.


In summary, the independent variable is what the researcher changes, and the dependent variable is what changes because of the alteration to the independent variable.



Example 1:  The researcher wants to determine the ergogenic effects of caffeine on baseball players’ performance.

  • Independent variable:  The level of caffeine being administered to the athletes.  The researchers may provide the players with a specific level of caffeine one day at practice and measure the results.  Then, on another day, a different level of caffeine is administered, the results are measured and compared to the previous level of caffeine.  This is the variable the researcher is controlling and changing.
  • Dependent variable:  The level of performance change as a result of the different levels of caffeine administered.  The researcher may measure the players’ 40-yard dash times, the distance they are able to throw the baseball, or the amount of weight they are able to bench press in the weight room.  These are all examples of different types of performance activities, any of which that may be the dependent variable.

Example 2:  The researcher wants to evaluate the amount of weight lost by the group on average based on various levels of calorie reduction.

  • Independent variable:  The reduction level of calories the participants consume daily will be the variable that changes.
  • Dependent variable:  The amount of weight lost by participants is changing in response to the varying levels of calorie deficits.

Example 3:  The researcher is examining the iron levels after participants follow a regular diet (consuming all animal foods), a vegetarian diet (consuming dairy and eggs, but no meat), or a vegan diet (consuming no animal foods).

  • Independent variable:  The diet assigned to the participants is what the researcher is changing.
  • Dependent variable:  The participants’ serum iron levels after following each of the diets.

Example 4:  A farmer wants to know which type of fertilizer helps his plants grow the fastest.

  • Independent variable:  The type of fertilizer the farmer chooses to provide to a section of plants.
  • Dependent variable:  The height and fruit growth of the plants based on the different type of fertilizer provided.


Final Thoughts on Dependent and Independent Variables

Constant variables:  A constant variable is a variable that remains the same during the course of the experiment.  Most experiments will have one independent variable and one dependent variable, but they will also have several constant variables.

Taking the first example above on testing the effects of caffeine on athletic performance, one constant variable might be the players’ diets.  We would want to make this constant for all.  Maybe they would all follow the same macronutrient distribution or all would eat the same foods provided in the meal halls.  This should be constant among the athletes because if one athlete consumes higher levels of carbohydrates (carbohydrate loads), his performance may be better than his teammates because of his improved diet.  Another constant is ensuring each athlete is well-hydrated.  If an athlete were dehydrated, his performance may be worse off than adequately-hydrated athletes.  In both cases, these should be made constant so we know the performance effects were not due to a superior diet or from dehydration, which could skew results.


How to chart dependent and independent variables:  The independent variable will always go on the x-axis, and the dependent variable will always go on the y-axis.  The title of the chart commonly follows the format of “[Independent Variable] vs. [Dependent Variable]”.

In the image above, you can see a sample chart for a study on caffeine levels and the effects on bench press in athletes.  The caffeine level (the independent variable) is listed on the x-axis, and the bench press weight (the dependent variable) is listed on the y-axis.  This chart illustrates as the level of caffeine goes up, the athlete’s bench press weight also increases, but that this seems to peak at 1.5 mg caffeine per kilogram of bodyweight and then begins to decrease.  Please note, this is only a made-up chart and not real data.