In a graph, the independent variable is typically placed on the x-axis (horizontal axis), while the dependent variable is placed on the y-axis (vertical axis). This arrangement helps to illustrate how changes in the independent variable affect the dependent variable. By convention, the independent variable is manipulated or controlled, while the dependent variable is measured in response.
line graph
The answer depends on the nature of the variables: for a start, whether they are qualitative or quantitative.
The Independent variable is placed on the x-axis and the dependent variable is placed on the y- axis
The two variables graphed on a coordinate graph are typically referred to as the independent variable and the dependent variable. The independent variable is plotted on the x-axis, while the dependent variable is plotted on the y-axis. This arrangement allows you to observe how changes in the independent variable affect the dependent variable.
The term that describes the relationship in which both the dependent and independent variables in a graph increase is called a "positive correlation." In a positively correlated relationship, as the independent variable increases, the dependent variable also tends to increase, indicating a direct relationship between the two. This is often represented by an upward-sloping line on a graph.
line graph
The scale in a graph is determined by the range of the dependent and independent variables.
Dependent variable take on X-axis and independent variable take on Y-axis in a graph.
The answer depends on the nature of the variables: for a start, whether they are qualitative or quantitative.
The Independent variable is placed on the x-axis and the dependent variable is placed on the y- axis
The two variables graphed on a coordinate graph are typically referred to as the independent variable and the dependent variable. The independent variable is plotted on the x-axis, while the dependent variable is plotted on the y-axis. This arrangement allows you to observe how changes in the independent variable affect the dependent variable.
A regression graph is most useful for predicting dependent variables, as it shows the relationship between the independent and dependent variables, allowing for the prediction of future values.
The independent variable (such as time) is places on the x-axis of a graph. Always place the things that will never change on the x-axis. The dependent variable is then placed on the y-axis. The difference between the independent and dependent variable is that the independent variable in an experient does not change it is what stays constent, it is what is used to measure the dependent variable. On the other hand the dependent variable is what the experiment is testing for and what depends on the independent variable.
To identify the dependent and independent variables in a graph, first look at the axes: the independent variable is typically plotted on the x-axis, while the dependent variable is on the y-axis. The independent variable is the one that is manipulated or changed to observe its effect, while the dependent variable responds to those changes. For example, in a graph showing the relationship between hours studied (independent) and exam scores (dependent), the exam scores depend on the number of hours studied. Observing the trend or pattern in the graph can also help clarify how these variables interact.
the dependent variable has one value and the independent variable has no value
The term that describes the relationship in which both the dependent and independent variables in a graph increase is called a "positive correlation." In a positively correlated relationship, as the independent variable increases, the dependent variable also tends to increase, indicating a direct relationship between the two. This is often represented by an upward-sloping line on a graph.
The independent variable causes changes in the dependent variable; the dependent variable is contingent on the manipulations of the independent variable.