2/29/2024 0 Comments Weak negative correlationMaternal age is continuous and usually skewed while parity is ordinal and skewed. That is, we are interested in the strength of relationship between the two variables rather than direction since direction is obvious in this case. The task is one of quantifying the strength of the association. We can expect a positive linear relationship between maternal age in years and parity because parity cannot decrease with age, but we cannot predict the strength of this relationship. Simple application of the correlation coefficient can be exemplified using data from a sample of 780 women attending their first antenatal clinic (ANC) visits. Hence, it would be inconsistent with the definition of correlation and it cannot therefore be said that x is correlated with y. It is possible to predict y exactly for each value of x in the given range, but correlation is neither −1 nor +1. This is so because, although there is a relationship, the relationship is not linear over this range of the specified values of x. In statistical terms, it is inappropriate to say that there is correlation between x and y. For example, consider the equation y=2×2. To emphasise this point, a mathematical relationship does not necessarily mean that there is correlation. 3 Any other form of relationship between two continuous variables that is not linear is not correlation in statistical terms. If, on the other hand, the coefficient is a negative number, the variables are inversely related (i.e., as the value of one variable goes up, the value of the other tends to go down). If the coefficient is a positive number, the variables are directly related (i.e., as the value of one variable goes up, the value of the other also tends to do so). The stronger the correlation, the closer the correlation coefficient comes to ☑. The strength of relationship can be anywhere between −1 and +1. A correlation coefficient of zero indicates that no linear relationship exists between two continuous variables, and a correlation coefficient of −1 or +1 indicates a perfect linear relationship. It is a dimensionless quantity that takes a value in the range −1 to +1 3. 1 Correlation is measured by a statistic called the correlation coefficient, which represents the strength of the putative linear association between the variables in question. In statistical terms, correlation is a method of assessing a possible two-way linear association between two continuous variables. Webster's Online Dictionary defines correlation as a reciprocal relation between two or more things 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). Misuse of correlation is so common that some statisticians have wished that the method had never been devised. This broad colloquial definition sometimes leads to misuse of the statistical term “correlation” among scientists in research. Among scientific colleagues, the term correlation is used to refer to an association, connection, or any form of relationship, link or correspondence. The term correlation is sometimes used loosely in verbal communication. Definitions of correlation and clarifications
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