## 4 Results of the Measurements and Analyses
### Probability Plots  
The mean R\({}_{\text{thaverage}}\) values for all the tested transistors were also compared. To this end, the Interval Plot was created in the Minitab and the results are presented in Figure 7b. The mean value of thermal resistance for the TRB_4 transistor position was R\({}_{\text{thaverage}}\) = 2.55 K/W. This value differs significantly from the thermal resistance value of the same type of transistor located in the position 2, where R\({}_{\text{thaverage}}\) = 2.19 K/W. Since the R\({}_{\text{thaverage}}\) results within one type of the TR_B transistor were significantly different, the results were analyzed in more detail using one of the T-test hypothesis tests. The T-test, also known as the Student's test, is used to compare the mean values of two groups of data. In our case, it concerns the average R\({}_{\text{thaverage}}\) values for the two positions of the transistors TR_B2 and TR_B4. However, it should be remembered that for this type of hypothesis test, it is important to assume that the possessed data distributions meet the normality condition. Therefore, in the first step, it was necessary to make sure that the distributions of the obtained R\({}_{\text{thaverage}}\) values for both the considered positions of the TR_B transistor meet these assumptions. For this purpose, in the Minitab, a normality test was performed using the Probability plot functions. The test result of the obtained R\({}_{\text{thaverage}}\) distributions for two positions of the transistor TR_B2 and TR_B4 is presented in Figure 8. In both the cases of distributions of R\({}_{\text{thaverage}}\) values, the parameter \(p\)-value > 0.05, and it was, respectively, for the TR_B transistor in position 2 with \(p\)-value = 0.357, and for the one in position 4 with \(p\)-value = 0.205. The statistically obtained distributions meet the assumptions of normality. The next step was to check whether the differences in the R\({}_{\text{thaverage}}\) variability of the TR_B transistor in positions 2 and 4 of the transistor are statistically significant. In the Minitab, a two-variance test was performed for this purpose. The result of this function is shown in the graph presented in Figure 9. This plot represents the confidence intervals for individual standard deviations for the R\({}_{\text{thaverage}}\) distributions of the transistors in positions  
Figure 8: Probability plot, R\({}_{\text{thaverage}}\) test of normality of the TR_B transistors located in the positions 2 and 4. Figure 7: Distribution of the thermal resistance value R\({}_{\text{th}}\) for individual TR_A and TR_B transistors located in individual positions 1–4 with the dissipated power P = 21.5W \(\pm\) 10% **(a)** Box plot and **(b)** Interval plot. 2 and 4. The obtained results show that the R\({}_{\text{thaverage}}\) value for the same type of transistor in position 4 has an estimated four times less variability compared with the transistor in position 2. In the last verification aimed at checking the real variability of thermal resistance R\({}_{\text{th}}\) due to the location of the tested transistors in the PCB module, the already described T-test (Student's test) was mentioned [34]. This test was performed in the Minitab program, which resulted in the tabular result presented in Table 3. The parameters in Table 3 are the following:  
* N--the number of samples you have;
* Mean--the average value of the obtained results of R\({}_{\text{thaverage}}\);
* StDev--the standard deviation;
* SE Mean--the standard error of the mean value (the basis for estimating the confidence interval of the mean value);
* T-value--the computed value of the hypothesis test statistic [28]. The most important result of the T-test was \(p\)-value = 0.023. This value is lower than 0.05, which allows us to reject the H0 hypothesis and go to the H1 hypothesis, concluding that the influence of one quantity on the other is significant.