在使用科学方法的任何实验中检查自变量和因变量，因此了解它们是什么以及如何使用它们非常重要。以下是独立变量和因变量的定义，每个变量的示例以及如何绘制图形的说明。自变量是您在实验中更改的条件。它是你控制的变量。它被称为独立的，因为它的值不依赖于实验中任何其他变量的状态，也不受其影响。有时您可能会听到称为“受控变量”的变量，因为它是被更改的变量。不要将它与“控制变量”混淆，后者是一个有意保持不变的变量，因此它不会影响实验的结果。因变量是您在实验中测量的条件。您正在评估它如何响应自变量的变化，因此您可以将其视为依赖于自变量。有时，因变量被称为“响应变量”。在一项确定学生睡眠时间是否会影响考试成绩的研究中，自变量是睡眠所花费的时间长度，而因变量是测试分数。你想比较纸巾的品牌，看看哪个最具流动性。您实验中的自变量将是纸巾的品牌。因变量是纸巾吸收的液体量。在确定人们可以看到光谱的红外部分的距离的实验中，光的波长是自变量以及是否观察到光（响应）是因变量。如果你想知道咖啡因是否会影响你的食欲，咖啡因含量的存在与否将是一个独立的变量。你有多饿是因变量。您想确定化学物质是否对大鼠营养至关重要，因此您需要设计一个实验。化学品的存在/不存在是独立变量。大鼠的健康（无论是生命还是可以繁殖）是因变量。如果您确定该物质是适当营养所必需的，则后续实验将确定需要多少化学物质。在这里，化学物质的量是独立变量，大鼠健康状况是因变量。如何分析独立变量和变量变量.如果您很难确定哪个变量是自变量而哪个是因变量，请记住因变量是受自变量变化影响的变量。如果在显示原因和结果的句子中写出变量，则自变量会对因变量产生影响。如果变量的顺序错误，则句子没有意义。独立变量会对因变量产生影响。示例：您睡眠的时间（自变量）会影响您的测试分数（因变量）。示例：您的考试成绩会影响您的睡眠时间。这实际上没有意义（除非你担心你没有通过考试，但这将是一个完整的其他实验）。
美国戴维森学院论文代写：独立和依赖变量
The independent variable and dependent variable are examined in any experiment using the scientific method, so it’s important to know what they are and how to use them. Here are the definitions for independent and dependent variables, examples of each variable, and the explanation for how to graph them. The independent variable is the condition that you change in an experiment. It is the variable you control. It is called independent because its value does not depend on and is not affected by the state of any other variable in the experiment. Sometimes you may hear this variable called the “controlled variable” because it is the one that is changed. Do not confuse it with a “control variable,” which is a variable that is purposely held constant so that it can’t affect the outcome of the experiment. The dependent variable is the condition that you measure in an experiment. You are assessing how it responds to a change in the independent variable, so you can think of it as depending on the independent variable. Sometimes the dependent variable is called the “responding variable.”In a study to determine whether how long a student sleeps affects test scores, the independent variable is length of time spent sleeping while the dependent variable is the test score. You want to compare brands of paper towels, to see which holds the most liquid. The independent variable in your experiment would be the brand of paper towel. The dependent variable would be the amount of liquid absorbed by a paper towel. In an experiment to determine how far people can see into the infrared part of the spectrum, the wavelength of light is the independent variable and whether the light is observed (the response) is the dependent variable. If you want to know whether caffeine affects your appetite, the presence/absence of amount of caffeine would be the independent variable. How hungry you are would be the dependent variable. You want to determine whether a chemical is essential for rat nutrition, so you design an experiment. The presence/absence of the chemical is the independent variable. The health of the rat (whether it lives and can reproduce) is the dependent variable. If you determine the substance is necessary for proper nutrition, a follow-up experiment would be to determine how much of the chemical is needed. Here, the amount of chemical would be the independent variable and the rat health would be the dependent variable. How To Tell the Independent and Dependent Variable Apart
If you are having a hard time identifying which variable is the independent variable and which is the dependent variable, remember the dependent variable is the one affected by a change in the independent variable. If you write out the variables in a sentence that shows cause and effect, the independent variable causes the effect on the dependent variable. If you have the variables in the wrong order, the sentence won’t make sense. Independent variable causes an effect on the dependent variable. Example: How long you sleep (independent variable) affects your your test score (dependent variable). Example: Your test score affects how long you sleep. This doesn’t really make sense (unless you can’t sleep because you are worried you failed a test, but that would be a whole other experiment).