*3.5. Statistical Significance Test*

After the model performance is measured, the model results can be found to not be statistically different from each other. This means that despite one model achieving results with a lower error in comparison to the next model's results, the model with the lower error does not necessarily outperform the model it is being compared to. A statistical test can be used to determine if model results are statistically significantly different. One such test is the t-test. The t-test uses the mean and the variance to check if two samples are from the same sample. The test calculates a significant value, also termed the *p*-value. A *p*-value less than the acceptable value means that the samples being compared have a significant difference, and vice versa. A *p*-value of 0.05, which is a commonly used value in scientific studies, was used in this study. The statistical significance test is performed, for each technique between the results with the lowest overall errors and results with the lowest errors from Exp 1, Exp 2, Exp 3, Exp 4, and/or Exp 5.
