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In statistics, correlation measures how strong the relationship is between two entities. A correlation of 1.0 means that the two move in perfect tandem with each other. A correlation of zero means that the relationship between them is totally random. A negative correlation, unusual in the investing world, means that they move in opposite directions. In investing, low correlation means that different asset types have not performed in the same way: When returns on some asset types were declining, returns on others were declining less, or indeed gaining. For investors, this diversification has obvious benefits: If poor performance in one investment can be offset by better (or even good) performance in another, extreme losses in an overall portfolio will be rarer than otherwise, and the capital will grow more in the long run.
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What is significance of correlation?
it shows any pattern that may emerge in any given set of date, this includes a positive or negative correlation. positive where a gradient goes from low to high negative where a gradient goes from high to low
What are the characteristics of a positive correlation?
First, a correlation is an indicator of the linear relationship between two events or manifestations. As such, it does not indicate that A causes B or B causes A, but rather that A and B coexists together. A correlation will vary between -1 and +1. A correlation of 0 will mean that there is no relationship between A and B. The closer the correlation is to the extreme, the stronger the relationship is. It is important to note that the sign only indicates whether the relationship is positive or negative. More specific to this question, a positive correlation will mean that as A increases, so does B. For example, perfectionism has been found to be positively correlated to depression. In other words, as the person presents more severe form of perfectionism, he or she will also show more symptoms of depression. This relationship could be represented in a graph as a diagonal line starting low and gradually moving higher as it moves towards the right.
Why correlation does not guarantee causation?
Correlation shows a possible relationship between two random variables. It does not say one variable causes a result in another. It further is wrong to conclude if event B occurs after event A, then A caused B. An example from Darrell Huff's book, "How to Lie with Statistics": A correlation is found between smoking and low grades. Does that mean that smoking causes low grades, or low grades cause people to smoke? It seems a good deal more probable that neither of these things produced the other, but that both are a product of some third factor. The inches of rain in Spain may correlate with the temperatures in Mexico, only because there is similarity of seasons. Small or improperly taken sample may show excellent correlations. The cumulative sum of births in China in one year (each day the total is the sum of all other previous days) will show an excellent correlation with the cumulative sum of rainfall in Germany. This correlation is because the the same values are repeated in the cumulative sums.
What is an example of correlation coefficient?
Correlation coefficient My understanding is: two variables as they relate to one another and how accurately you can predict their behavior to one another when together. Basically the strength of the linear association between two variables. When the variables have a tendency to go up and down together, this is a positive correlation coefficient. Variables with a tendency to go up and down in opposition, (one ends up with a high value and the other a low value) this is negatiove correlation coefficient. An example would be the amount of weight a mom gains during pregnancy and the birth weight of the baby
What does a low mean deviation means?
A low standard deviation would mean that there is not much variation from the mean value of the data.
