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Normality of data (x) was tested using the Kolmogorov-Smirnov test and the homogeneity of variances was checked using the Levene's test.
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During the test stage, a test data x is scored using the following equation, mathbf{f}(mathbf{x}) = mathbf{h}(mathbf{x}) boldsymbol{beta} = mathbf{h}(mathbf{x}) (mathbf{H}^{T} mathbf{H})^{-1} mathbf{H}^{T} mathbf{T} (7).
During the test stage, a test data x is scored by the following equation, begin{array}{*{20}l} mathbf{f}(mathbf{x}) & = mathbf{h}(mathbf{x}) boldsymbol{beta} end{array} (18).
Normality of the data was tested with Shapiron-Wilk test.
First, data was tested for normal distribution.
In this analysis, GBS data with the whole range of x and SNP array data were tested (see Subsection " Marker genotypes").
For example, the prediction of the average against left handed pitchers in the ballpark X could be tested on data from a different month.
All data sets were tested for normality.
All data were tested for normality using a Shapiro-Wilks test, with Gd3+ data log(x) transformed and chloral hydrate data square root transformed.
The data are still being tested.
Data were tested for normal distribution.
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