The second is halved.
Variables allow one to summarise a lot of information using just a variable and a related function.
A correlation is the relationship between two or more variables. Correlations are described as either weak or strong, and positive or negative. There can be a perfect correlation between variables, or no correlation between variables. It is important to determine the correlation between variables in order to know if and how closely changes in one variable are reflected by changes in another variable. This is done by determining the coefficient of correlation (r), which describes the strength of the relationship between variables and the direction. -1 ≤ r ≤ +1 if r= +1 or -1, there is a perfect correlation if r= 0 there is no correlation between the variables. a value closer to + or - 1 demonstrates a strong correlation, while a value closer to 0 demonstrates a weak correlation. a + value demonstrates that when one variable increases the other variable increases, while a - value demonstrates that when one variable increases the other variable decreases. However, it is very important to understand that correlation is not the same as relationship. Consider the two variables, x and y such that y = x2 where x lies between -a and +a. There is a clear and well-defined relationship between x and y, but the correlation coefficient r is 0. This is true of any pair of variables whose graph is symmetric about one axis. Conversely, a high correlation coefficient does not mean a strong relationship - at least, not a strong causal relationship. There is pretty strong correlation between my age and [the log of] the number of television sets in the world. That is not because TV makes me grow old nor that my ageing produces TVs. The reason is that both variables are related to the passage of time.
Correlation between two variables implies a linear relationship between them. The existence of correlation implies no causal relationship: the two could be causally related to a third variable. For example, my age is correlated with the number of TV sets in the UK but obviously there is no causal link between them - they are both linked to time.
Hypothesis
It is the constant of proportionality.
If the variables are inversely related, doubling one will half the other.
A negative correlation means that two variables are inversely related. This means that as one variable increases the other decreases. When a negative correlation is plotted, it forms a downward slanting line.
if two variables are positively related,it means that the two variables change in the same direction.that is,if the value of one of the variables increases,the value of the other variable too will increase.for example,if employment as an economic variable increases in a country,and price of goods too increases then we can say that these two variables(employment and price) are positively related
Independent variables can take values within a given boundary. The dependent variable will take values based on the independent variable and a given relationship at which the former can take its values.
a DEPENDENT variable is one of the two variables in a relationship.its value depends on the other variable witch is called the independent variable.the INDEPENDENT variable is one of the two variables in a relationship . its value determines the value of the other variable called the independent variable.
Independent variables can take values within a given boundary. The dependent variable will take values based on the independent variable and a given relationship at which the former can take its values.
The variables are said to be INVERSELY related.
An inverse relationship is one in which as the value of one variable increases, the value of the second variable decreases. For example, in the equation y = 1/x, as y gets bigger, x gets smaller and as x gets bigger, y gets smaller.
Algebraic expressions may contain variables but they are not normally called variables. In fact, if they are related to identities, they need not be variable. For example, (4x2 + 8xy + 4y2)/(x + y)2 is an algebraic expression, but it is not a variable: it equals 4.
an independent variable is a variable that changes the dependent variable.___________________________________________________Independentvariableis:a factor or phenomenon thatcausesorinfluencesanotherassociatedfactor or phenomenon called adependent variable. For example,incomeis an independentvariablebecause it causes and influences another variableconsumption. In a mathematicalequationormodel, the independent variable is the variable whosevalueis given. In anexperiment, it is the controlledcondition(that is allowed tochangein asystematicmanner) whose effect on thebehaviorof a dependent variable is studied. Also calledcontrolled variable,explanatory variable, orpredictor variable.
The steps are to find the y-axis (dependent variable) and the x-axis (independent variable), then make a scale for your variables on the graph.
Variables allow one to summarise a lot of information using just a variable and a related function.