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If anxiety and depression are correlated what three possible directions of causality might explain this correlation?
Wiki User
∙ 9y ago
If anxiety and depression are correlated, there are three possible directions of causality. These are anxiety causes depression, depression causes anxiety, and there is an environmental stimuli that causes both anxiety and depression.
Wiki User
∙ 9y ago
jany66960
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Does correlation prove causality?
No. If Factor X is correlated to Factor Y then you can use one as a predictor of the other, but you should never assume that one causes the other (it may, but correlation alone doesn't prove it).Consider the correlation between proximity to a swampland and chances of contracting malaria. Do swamplands cause malaria? No. Malaria is propagated via mosquitoes which of course love to live in swamplands. So your proximity to a swampland is a useful predictor of your chances of contracting malaria, but doesn't cause it.
How is saying that two variables are correlated different from saying saying that one caused the other?
Correlation and causality are not necessarily related. My age is pretty well correlated with the number of TV sets in the world. But neither of them is caused by the other. In this particular example, they both happen to be correlated to time, but there need not be such a factor. Conversely, let y = x2. Compile a set of pairs of x values, x = -m and x = +m and the corresponding y values, m2. Now, y is totally defined by x, but the correlation of y with x (not x2) for the above set of values will be zero. In this example x causes y but the relationship is not linear - the model is wrongly specified.
What Key word do you associate with sequence of events and what rules of probability do you use?
The key word that I use is causality. However, you cannot use probability to determine causality. Even if two events are highly correlated, probability theory cannot tell whether event A is caused by event B, or event B is caused by event A, or that both are caused by some third event that is not even part of the study.
What rhymes with the word causality?
morality
What is the definition of circular causality?
Circular causality refers to a series of events where each one is caused by the one before it, and the first one is caused by the last.
Does correlation prove causality Briefly explain?
No. The correlation between two variables implies that one of them can be predictor of the other. That is, one variable helps to forecast the other and it is not causality.
Does correlation prove causality?
No. If Factor X is correlated to Factor Y then you can use one as a predictor of the other, but you should never assume that one causes the other (it may, but correlation alone doesn't prove it).Consider the correlation between proximity to a swampland and chances of contracting malaria. Do swamplands cause malaria? No. Malaria is propagated via mosquitoes which of course love to live in swamplands. So your proximity to a swampland is a useful predictor of your chances of contracting malaria, but doesn't cause it.
Correlations are an indication that causality is always present?
False. One of the most important rules to learn in statistics is that correlation does not equal causation. Just because two items or correlated, or linked, doesn't necessarily mean that one caused the other. For example, think about if every time you go out for a run it starts raining. Those two events may be correlated, but that doesn't mean you cause it start raining because you went for a run.
How is saying that two variables are correlated different from saying saying that one caused the other?
Correlation and causality are not necessarily related. My age is pretty well correlated with the number of TV sets in the world. But neither of them is caused by the other. In this particular example, they both happen to be correlated to time, but there need not be such a factor. Conversely, let y = x2. Compile a set of pairs of x values, x = -m and x = +m and the corresponding y values, m2. Now, y is totally defined by x, but the correlation of y with x (not x2) for the above set of values will be zero. In this example x causes y but the relationship is not linear - the model is wrongly specified.
Correlation coefficient value mean?
The correlation coefficient is a measure of linear association between two (or more) variables. It does not measure non-linear relationships nor does it say anything about causality.
When two factors are correlated a cause and effect relationship exists between the factors?
Nope, correlation simply links two factors together, while a cause and effect relationship finds that one factor causes change in the other. Generally, cause and effect is harder to establish and requires more clinical rigour (eg. with experiments).
What is the difference between cause and correlation?
Correlation means that two events are related. Causation means that one event caused another event to happen. Correlation isn't the same as causation.
What is the correlation between two quantities?
It is a measure of the extent to which a linear change in one quantity is accompanied by a linear change in the other quantity. Note that only linear changes are measured and that there is no causality.
What is correlation coefficient?
'Correlation coefficient' means a statistic representing how closely two variables co-vary; it can vary from -1 (perfect negative correlation) through 0 (no correlation) to +1 (perfect positive correlation)* * * * *A key piece of information that is left out of the answer by True Knowledge (which casts very serious doubts about its name!) is that the statistic only is a measure of linearrelationship. A symmetric non-linear relationship (a parabola, for example) will show zero correlation but show anyone a graph of a parabola and then try convincing them that there is no relationship between the two variables!A correlation for two variables is a measure of the strength of a linear relationship between them. It is a measure that ranges from -1 (the variables move perfectly together but in opposite directions) to 1 (the variables move perfectly together and in the same direction). A correlation coefficient of 0 indicates no linear relationship between the variables.Two important points to note:Correlation measures linear relationship: not any other relationships. Thus a perfect relationship that is symmetric (y = x^2, for example) will have a correlation coefficient of 0.Correlation coefficient is a measure of association, not of causality. In the UK, ice cream sales and swimming accidents are correlated. This is not because eating ice cream causes swimming accidents not because people recover from swimming accidents by eating ice cream. In reality, both events are more likely on warm days - such as they are!
Why cant correlational studies show causality between two variables?
Correlation can only show that one variable increases linearly as another increases or decreases. It cannot show non-linear relationships. There can, therefore, be a perfect non-linear relationship and the correlation coefficient can be zero. For example y = x2 in the range (-a, a) for any positive number a, Second, correlation cannot determine whether A causes B or B causes A. There is probably a good correlation between my age over the last 10 years and the number of white hairs on my head. However, I do not think that white hairs caused me to GROW older (I may look older, but that is another matter entirely). Furthermore, when there are two correlated variable, there may not be any causal relationship between the two variables but there may be a third variable that causes both. There is a fairly good correlation between my age and the number of cars in the UK. My growing old did not increase the number of cars and the number of cars did not make me grow old. So there is no causal relation between them. Instead, both are correlated to time.
What is the implication of any correlation found 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.
Why do economists often say that correlation does not necessarily imply causality?
It's not only economists that offer this warning. It's true anywhere that correlation coefficients are to be interpreted. Let me offer an example from psychology. In many populations there's a significant correlation between the shoe sizes of people and their intelligence quotients. But no-one would say that increasing a person's shoe size would increase their intelligence!
