Example No.12

Enter data:  

Body weight (x_i) : 2.2, 1.8, 2.1, 1.7, 2.4, 2.0, 2.0, 1.9, 2.3, 1.9 [kg]

Egg weight (y_i): 41, 36, 40, 36, 42, 39, 40, 37, 41, 38 [g]

1) Calculation of mean values:   

Results:  Body weight: 2.030 kg

                Egg weight: g

2) Calculation of coefficients in equation of linear regression (y=bx + a):

Result: Linear regression y = 9.29705x + 20.12698

4) Calculation of significance of the correlation coefficient:

                           DF = n-2 = 8

As calculated t > t_crit= 3.355 (DF=8, α=0.01) the correlation coefficient is statistically highly significant. 

Conclusion: between body weight of layers and weights of their eggs the relation was found that is described by means of linear regression y = 9.29705x + 20.12698 and correlation coefficient 0.9527 that is statistically highly significant (p<0.01).

Note:

Both variables monitored in this example are equally valuable, then its relation is reciprocal (correlative relation) and it is possible to evaluate it also by means of the method, based on the mutual exchange of data sets (X« Y).

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