Want this question answered?
If they increase or decrease exactly, then the constant of proportionality or coefficient of proportionality. If not exactly, then a correlation coefficient.
Two variables, x and y are said to be in direct variation with one another if they are related by an equation of the form y = cx where c (>0) is the constant of [direct] variation. In the coordinate plane, this equation gives rise to a straight line, through the origin, and with a gradient (slope) = c. What this means that both x and y are 0 together, and that every increase (or decrease) in x results in an increase (decrease) of c times that amount in y.
Correlation analysis seeks to establish whether or not two variables are correlated. That is to say, whether an increase in one is accompanied by either an increase (or decrease) in the other most of the time. It is a measure of the degree to which they change together. Regression analysis goes further and seeks to measure the extent of the change. Using statistical techniques, a regression line is fitted to the observations and this line is the best measure of how changes in one variable affect the other variable. Although the first of these variables is frequently called an independent or even explanatory variable, and the second is called a dependent variable, the existence of regression does not imply a causal relationship.
It tells you that the two variables in the graph change together at the same rate. There may or may not be a causal relationship between the tw variables: both could be related to a third variable which is not part of the graph.
"In curvilinear relationships, the data points increase together up to a certain point (like a positive relationship) and then as one increases, the other decreases (negative relationship) or vice versa." A linear relation is very simple: if one variable goes up, the other goes up (positive correlation) or goes down (negative correlation). A curvilinear relation between variables is non-linear (i.e., that cannot be described by a straight line). Basically, anythig not linear is curvilinear.
Are in direct proportion
It means that there is a strong positive association between changes in the two variables being studied. Positive association means that the two variables tend to increase together or decrease together. Note that there is no mention of a causal relationship between the variables.
Correlation is a measure of the degree to which two variables change together. Positive correlation means that the variables increase together and decrease together. Negative correlation means that one variable increases when the other decreases.Correlation does not imply causality.Correlation is a measure of the degree to which two variables change together. Positive correlation means that the variables increase together and decrease together. Negative correlation means that one variable increases when the other decreases.Correlation does not imply causality.Correlation is a measure of the degree to which two variables change together. Positive correlation means that the variables increase together and decrease together. Negative correlation means that one variable increases when the other decreases.Correlation does not imply causality.Correlation is a measure of the degree to which two variables change together. Positive correlation means that the variables increase together and decrease together. Negative correlation means that one variable increases when the other decreases.Correlation does not imply causality.
Direct variation
It is a positive relationship.
It implies that an increase in x is accompanied by an increase in y. And similarly, they decrease together.
If they increase or decrease exactly, then the constant of proportionality or coefficient of proportionality. If not exactly, then a correlation coefficient.
Variation in direct proportion.
The relationship between two quantities that increase or decrease together is called a positive correlation. This means that as one quantity increases, the other quantity also increases, and vice versa.
direct variation or positive correlation.
The value of a correlation coefficient reflects the strength and direction of the relationship between two variables. A correlation coefficient ranges from -1 to 1, with 1 indicating a perfect positive relationship, 0 indicating no relationship, and -1 indicating a perfect negative relationship.
If the correlation is positive, as one increases so does the other.