Correlation is a measure of fluctuation between two or more variables together and can either be positive or negative. On the other hand, causality is a cause-effect phenomenon where the measure of one event decreases or increases due to the introduction or application of another or other events. Correlation is a relationship whereas causality is a cause-and-effect. For instance, a correlation may appear between drug abuse and crime, in that both occur in high or low levels in the same population. It is however statistically invalid to presume that drug abuse causes crime or that crime causes drug abuse without investigating the effect of another variable or variables (Triola, 2006).
Y = Β0 + Β1X is a population parameter whose values of B0 (a constant) and B1 (the regression coefficient of X) are estimated by use of the sample statistic regression equation ŷ = b0 + b1x. Y indicates the value of the outcome variable whereas ŷ indicates the estimated value of the outcome variable. It, therefore, follows that Y is a fixed, unknown population characteristic that can only be estimated using ŷ, a known characteristic of the sample (Triola, 2006).
The geneticist can use a nonlinear regression model. The nonlinear model is more flexible in the types and shapes of curves it can fit appropriately. It is however important for the geneticist to use a linear regression model first and eval…
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