Prediction of the length and width of quail eggs using linear regression analysis
<b>Aim:</b> This study was aimed at establishing regression equations for the estimation of egg length and egg width values using egg weight values in quail eggs, and at determining the error rate of the regression equations established.<p> <b>Materials and Methods:</b>...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Selcuk University Press
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| Series: | Eurasian Journal of Veterinary Sciences |
| Subjects: | |
| Online Access: | http://eurasianjvetsci.org/pdf.php3?id=1257 |
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| Summary: | <b>Aim:</b> This study was aimed at establishing regression equations
for the estimation of egg length and egg width values
using egg weight values in quail eggs, and at determining the
error rate of the regression equations established.<p>
<b>Materials and Methods:</b> Quail eggs were collected twice,
between June and August to be used for the establishment of
equations, and between September and October to be used
for the assessment of the accuracy of the equations established.
The numeric measurements of the eggs are presented as
means and standard deviations.<p>
<b>Results:</b> Equations were established for the estimation of
the dependent egg length and egg width variables using
the independent egg weight variable with linear regression
analysis. It was determined that equations (1) and (2) established
for the estimation of egg length and egg width, respectively,
both performed very well. The R² value was 0.99
for both equations, which demonstrated that the egg weight
variable had a share of 99% in describing the total change in
the egg length and egg width variables. The mean difference
between the regression equation established in this study
for the estimation of egg length and the Rahn and Paganelli
(1988) equation was found to be statistically insignificant
(P=0.939).<p>
<b>Conclusion:</b> In result, the regression equation established in
this study for the estimation of quail egg width was ascertained
to perform better than the Rahn and Paganelli (1988)
equation, and the mean difference between these two equations
was statistically significant. |
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| ISSN: | 1309-6958 2146-1953 |