Is this a literature theory - According to Mishra et al., (2019), "Student's t test (t test), analysis of variance (ANOVA), and analysis of covariance (ANCOVA) are statistical methods used in the testing of hypothesis for comparison of means between the groups. In each of these approaches, the aim is to establish whether the variations in means have statistical significance, which would provide support for the hypothesis under investigation. A common approach used by academics is to utilize the paired t-test to assess the average discrepancy between corresponding data points. Regrettably, this test is often ineffective (Hedberg & Ayers, 2015). This sentiment was echoed Langenberg et al., (2023), who affirms that "For designs that only involve factors with two levels each, the paired t test can be used for power calculations, but some pitfalls need to be avoided." Authors Yu et al., (2022) explained that, "The most widely used methods such as t test and ANOVA do not take data dependence into account and thus are often misused" (p.1). Yu et al. recommended that using "mixed-effects models" can enhance the methodology of experiments and result in more valid and reproducible data analysis" (p.1). Therefore, utilizing Analysis of Covariance, or ANCOVA, can enhance the accuracy of a T-test. Thus, employing Analysis of Covariance, or ANCOVA, can improve the precision of a T-test. It is used to take into account for the variability caused by multiple factors that may affect the depe