## 4 Discussion  
The change of heat transfer coefficients during the time of the experiment was evaluated first for each sample individually. These changes followed a model of linear regression and the evaluation is summarized in Tables 2 and 3 and Figure 6.  
The differences between the control sample and the sample modified at 160 \({}^{\circ}\)C, as can be deducted from Table 2, were in the range of -5%. The differences between the samples treated at 160 \({}^{\circ}\)C and 180 \({}^{\circ}\)C were in range of 5-9%. Between the samples modified at 180 \({}^{\circ}\)C and 200 \({}^{\circ}\)C, the difference ranged between 6-25% for 200 \({}^{\circ}\)C and 16-17% for 220 \({}^{\circ}\)C. According to the results in Table 2, the difference range was smaller at the end of the experiment (\(\alpha=8.6-5.5\) Wm-2K-1) than at the beginning (\(\alpha=22.66-11.61\) Wm-2K-1). \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Sample (Mean)**} & \multirow{2}{*}{\
\begin{tabular}{c} **Data** \\ **Normality** \\ **\(p\)-level** \\ \end{tabular} } & \multirow{2}{*}{
\begin{tabular}{c} **Variance** \\ **Analysis,** \(p\) \\ \end{tabular} } & \multicolumn{2}{c}{**Tuckey HSD Unequal Sample Size Significance Test**} \\ \cline{4-7}  & & & **Control** & **160 \({}^{\circ}\)C** & **180 \({}^{\circ}\)C** & **200 \({}^{\circ}\)C** & **220 \({}^{\circ}\)C** \\ \hline Control (15.63) & 0.260 & & & 0.996 & 0.104 & 0.000 & 0.000 \\
160 \({}^{\circ}\)C (15.25) & 0.128 & & 0.996 & & 0.229 & 0.000 & 0.000 \\
180 \({}^{\circ}\)C (14.21) & 0.040 & 0.000 & 0.104 & 0.229 & & 0.045 & 0.000 \\
200 \({}^{\circ}\)C (11.19) & 0.010 & & 0.000 & 0.000 & 0.045 & & 0.040 \\
220 \({}^{\circ}\)C (0.52) & 0.237 & & 0.000 & 0.000 & 0.000 & 0.040 & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Analysis of variance (ANOVA) between heat transfer coefficients of samples with different treatment results. Figure 7: Box plot of 95% confidence intervals of the mean heat transfer coefficient \(\alpha\) at tested treatment levels. In Figure 6, it is shown that the value of the heat transfer coefficient \(\alpha\) for all samples of the thermally modified wood was lower than the value corresponding to the control sample. In the observed range, the change of the heat transfer coefficient during heating could be described by a significant linear regression. As is visible in Figure 6, the \(\alpha\) coefficients decreased with heating time. The same could be conducted from the correlation coefficients shown in Table 3. All samples showed \(r<-0.94\). The proximity of this coefficient to the value \(-1\) indicated that the correlation was significant and the fact that this coefficient was negative meant that the correlation was negative; \(\alpha\) decreased with time. From the \(t\)-test of the regression coefficient with the \(p\)-level shown in Table 3, a large significance could be stated for the use of the linear model. The coefficients of determination \(R^{2}\) from Figure 6 showed that an appropriate model was used. For the sample treated at 160 \({}^{\circ}\)C, \(R^{2}\) = 0.99 meant that 99% of values were described by the model with the remaining 1% considered as random influences. For the control and the 180 \({}^{\circ}\)C samples, the determination coefficient totaled \(R^{2}\) = 0.94. For 200 \({}^{\circ}\)C and 220 \({}^{\circ}\)C, the result was \(R^{2}\) = 0.93. In the second part of the data evaluation, a variation analysis (ANOVA) was used to prove the significance of the thermal modification effect on the heat transfer coefficient of wooden samples. The results of this analysis are summarized in Table 4 and Figure 7.  
As shown in Table 4, the control sample and the 160 \({}^{\circ}\)C, 180 \({}^{\circ}\)C and 220 \({}^{\circ}\)C samples passed the test of data distribution normality. According to the Tuckey test results in Table 4, the most significant differences occurred between the untreated control sample and the 200 \({}^{\circ}\)C and 220 \({}^{\circ}\)C samples with confidence nearing 100%.