an example of third variable correlation would be something like a lack of adult supervision (the 3rd variable) would cause watching televised violence and aggressiveness. There are still two other variables that are in relation to each other, but they probably would not occur unless the 3rd variable was there (which is the lack of parents).
coorelation
Utilities
A variable means that something that you can change, measure, or keep the same. Example: Responding variable: The variable you can measure. Controlled variable: The variable you keep the same. Manipulated variable: The variable that you change.
A dependent variable is what you measure in the experiment and what is affected during the experiment. The dependent variable responds to the independent variable. It is called dependent because it "depends" on the independent variable. In a scientific experiment, you cannot have a dependent variable without an independent variable. Example: You are interested in how stress affects heart rate in humans. Your independent variable would be the stress and the dependent variable would be the heart rate. You can directly manipulate stress levels in your human subjects and measure how those stress levels change heart rate.
What is changed, either by you or the different results. The mother-category of the IV and DV. (independent VARIABLE, and dependent VARIABLE) :)
Spurious Correlation.
Any variable can be a correlation variable. In some cases there may be no apparent correlation but that, in itself, that means nothing. For example, the x and y coordinates in the equation of a circle (or any symmetric shape) are not correlated. On the other hand, there is a pretty good correlation between my age and the number of cars in the world.A correlation variable is simply a variable that you study to see if changes in the variable that you are interested in is, in any way, related to changes in the correlation variable, and to get some idea of the degree to which they move in line.
This would be an example of a negative correlation, where as one variable (air temperature) increases, the other variable (activity of test animals) decreases.
Correlation determines relationship between two variables. For example changes in one variable influence another variable, we can say that there is a correlation between the two variables. For example, we can say that there exists a correlation between the number of hours spent on reading and preparation and the scores obtained in the examination. One can infer that higher the amount of time spent on preparation may result in better performance in examination leading to higher scores. Hence the above is a case of positive correlation. If an increase in independent variable leads to an increase in dependent variable, it is a case of positive correlation. On the other hand if an increase in independent variable leads to a reduction in dependent variable, it is a case of negative correlation. An example for negative correlation could be the relationship between the age advancement and resistance to diseases. As age advances, resistance to disease reduces.
Things may be correlated without causal relationship or conversely. Consider the Modulus function - that is the value of a number without regard to its sign. Over any domain (-a,a), there is a very strict relationship between x and mod(x), but their correlation is 0. Conversely, I expect that there is a good correlation between my age and the number of TV sets in the world. That is not to say that my getting older is producing more TVs or that TV production is causing me to age. Simply that both of them are correlated to a third variable - time. There can be correlation without such a third variable but, offhand, I cannot think of an example.
The third variable could be one which is correlated to both variables. These are called confounding variable. For example, in the UK you could find a correlation between coastal air pollution and ice cream sales. This is not because eating ice cream causes air pollution nor because air pollution causes people to eat ice cream. The confounding variable is the temperature. Warm weather gets people to drive to the sea!
a. The correlation between X and Y is spurious b. X is the cause of Y c. Y is the cause of X d. A third variable is the cause of the correlation between X and Y
That is a negative correlation in psychology. It means that as one variable goes up, the other variable goes down.
A positive correlation between two variables means that there is a direct correlation between the variables. As one variable increases, the other variable will also increase.
Correlation occurs when two variables are related or co-vary in a systematic way. This means that as one variable changes, the other variable tends to change in a particular direction. Correlation can happen due to a direct cause-and-effect relationship or because both variables are influenced by a common third factor.
No correlation.
As one variable increases the other variable decreases.