Correlation between length and weight Name Institutional affiliations Correlation between length and weight This paper aims at discussing the statistical ways in which the relationship between the weight and length of bears can be analyzed. The relationship weight (W) and length (L) for almost all bears can be presented by the Weight and length relationship -W = qLb (1.1). Null Hypothesis: There is no statistical significance between length and weight Alternative hypothesis: There is a statistical significance relationship between length and weight Where W and L represent the weight and length of the bears while ‘q ‘and ‘b' represent constants. The constant ‘b' indicates the rate of weight gain in relation to the length growth or the rate at which the weight of the bear increases with an increase in length. The constants q and b can be estimated by use of linear functions. However, as observed in ecological setups, these functional relationships tend to be non-linear. For instance, in our case, the weight-length relationship is non-linear. This nonlinear functions (Curvilinear) relationships can be easily be transformed to linear functions by converting both sides to natural logarithms (Brase & Brase, 2009). Ln W= ln q+ b.ln L (1.2). The above equation is equal to the linear regression equation given below. Y=a+b*x(1.2a) The interpretation of this equation is that; Y is equal to ln W, which represents the y-intercept (this is the point where the line cuts the y-axis). The regression line is equivalent to ln q, b is the gradient, and x is equivalent to ln L. This now makes it easier for one to estimate the values of a and b by use of linear

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