If two continuous measures are positively correlated with one another, does that mean that one of...

If two continuous measures are positively correlated with one another, does that mean that one of them caused the other? Why or why not?If two continuous measures are positively correlated with one another, does that mean that one of them caused the other? Why or why not? (THIS IS FOR MY MKT RESEARCH CLASS)

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Correlation is a statistical method that determines the degree of relationship between two different variables. It is also known as a “bivariate” statistic, with bi- meaning two and variate indicating variable or variance. The two variables are usually a pair of scores for a person or object. The relationship between any two variables are can vary from strong to weak or none. When a relationship is strong, this means that knowing a person's or object’s score on one variable helps to predict their score on the second variable.

When the correlation coefficient approaches r = +1.00 (or greater than r = +.50) it means there is a strong positive relationship or high degree of relationship between the two variables. This also means that the higher the value of one variable, the higher the value will be on the other variable. For example, there is a positive correlation between years of education and wealth. Overall, the greater the number of years of education a person has, the greater their wealth. A strong correlation between these two variables also means the lower the number of years of education, the lower the wealth of that person. If the correlation was perfect one (r = +1.00), then there would be not a single exception in the entire sample to increasing years of education and increasing wealth. It would mean that there would be a perfect linear relationship between the two variables. However, perfect relationships do not exist between two variables in the real world of statistical sampling. Thus, a strong but not perfect relationship between education and wealth in the real world would mean that the relationship holds for most people in the sample but there are some exceptions. In other words, some highly educated people are not wealthy, and some uneducated people are wealthy.

orchestra answered 1 year ago

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