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When the graph of best fit is a straight line the dependent and independent variables are?
When the graph of best fit is a straight line, the relationship between the dependent and independent variables is linear. This indicates that as the independent variable changes, the dependent variable changes at a constant rate. In other words, a change in the independent variable results in a proportional change in the dependent variable. This linear relationship can often be expressed with the equation of a line, typically in the form (y = mx + b), where (m) is the slope and (b) is the y-intercept.
What else can I help you with?
Which graph is best for analyzing quantitive independent and dependent variables?
line graph
How to graph independent and dependent variables?
The answer depends on the nature of the variables: for a start, whether they are qualitative or quantitative.
What does a straight line mean on a line graph?
That there is a linear relationship between the dependent and independent variables
What term describes the relationship in which the dependent and independent variables in a graph both increase?
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.
A straight line on a graph means there is a relationship between the dependent variable and the independent variable?
_linear_
When the graph of best fit is a straight line the dependent and independent variables have what kind of relationship?
the dependent variable has one value and the independent variable has no value
Which graph is best for analyzing quantitive independent and dependent variables?
line graph
The scale in a graph is determined by?
The scale in a graph is determined by the range of the dependent and independent variables.
How to graph independent and dependent variables?
The answer depends on the nature of the variables: for a start, whether they are qualitative or quantitative.
What type of graph is most useful for making predictions about dependent variables?
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.
What does a straight line mean on a line graph?
That there is a linear relationship between the dependent and independent variables
What term describes the relationship in which the dependent and independent variables in a graph both increase?
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.
On a graph of two variables which is the variable that causes changes in the other?
The independent variable causes changes in the dependent variable; the dependent variable is contingent on the manipulations of the independent variable.
What are the differences between independent and dependent variables?
Independent variables are controlled or manipulated by the researcher to determine their effect on the dependent variable. Dependent variables, on the other hand, are the outcome or response that is measured in an experiment. The independent variable causes a change in the dependent variable.
A straight line on a graph means there is a relationship between the dependent variable and the independent variable?
_linear_
A straight line on a graph means there is a relationship between the dependent variable and the independent variable.?
_linear_
When is a bar graph useful?
when a sets of data can be separated by 2 orders of variables, which are the independent & dependent variables.
