Profile of the Participants

Fifteen participants comprised 11 females (73.33%) and 4 males (26.67%). The mean and median ages of the participants are 20 years old, while the mode age is 21 years old. Among the participants were all college students, 8 (53.33%) were from BS PSY of LAAO, 6 (40%) from BSN of NAO, and 1 (6.67%) from AEET of SITAO.

According to the collected data, some participants had the lowest scores of 4, while others had 8 and the highest scores of 9, respectively. Also, it can be asserted that out of the fifteen participants, it is noteworthy that the average score ranges between 5 and 6, despite the fact that the majority of them tended to be inclined toward 6 as the median point. This just describes the midpoint of their cognitive performance or aptitude; it does not imply that their capacity is restricted to 5 or 6.

Table 1. Classical Music

The data in the table demonstrates that five participants achieved up to level 5 (33.3%), four participants earned up to level 6 (26.7%), three participants obtained up to level 7 (20.0%), two participants managed up to level 4 (13.3%), and one participant scored up to level 8 (6.7%). It suggests that when using the variable of classical music, the majority excelled on level 5, while it is uncommon to thrive on level 8.

Table 2. Brown Noise

As shown in the table, six individuals got a level 5 score of 40.0%, three people from levels 6 and 8 achieved a percentage of 20.0% each, two participants reached a level 7 score of 13.3%, and one participant earned a level 4 score of 6.7%. It indicates that most participants performed well on level 5, similar to classical music, while a particular participant also did well on level 4.

Table 3. White Noise

As noted in the table, six participants achieved a level 5 score (40.0%), four participants reached a level 7 score (26.7%), two persons achieved percentages of 13.3% at levels 4 and 6, and one participant got a level 9 score (6.7%). It signifies that while the majority of participants achieved levels of performance, it is also vital to take into account that using white noise as a variable for cognitive performance makes it feasible to achieve the highest possible score.

Table 4. Ambient Sound

It is clear from the table that six participants achieved level 6 (40.0%), five participants achieved level 5 (33.3%), two participants achieved level 8, and one person each at level 4 and level 7 received a 6.7%. It demonstrates that, in contrast to the three variables discussed, a significant number of participants scored up to level 6. It's nonetheless significant to note that some people appeared to score lower at levels 4, 7, and 8. This is probably due to the sounds that affect their cognitive performance rather than because they have weak cognitive ability.

Based on the data established, it was revealed that the data is non-significant when utilizing Mauchly’s test (W =.679, p =.426). Thus, it is reasonable to conclude that the variances of the differences are not significantly different. This indicates that the data are roughly equal, and sphericity can be directly assumed.

It was demonstrated that since p =.426, as stated above, it can be deduced that the requirement of sphericity has been met, so no correction to the F-value is needed. Therefore, the "None" Sphericity Correction output values for the repeated measure were employed ‘Task’: F = .239, df = 3, p =.869. Also, it was implicated that various sounds did not significantly affected the performance when performed, (F (3, 42) = .239, p = .426, η²G=.007).

The Tukey's Post Hoc Test indicated there was no significant difference between classical music, brown noise, white noise, and ambient sound because it showed that P_tukey exceeded .05 that supports the idea that the significance level has no significant difference.

Ultimately, Estimated Marginal Means for various sounds showed classical music (mean = 5.73), brown noise (mean = 6.00), white noise (mean = 5.80), and ambient sound (mean = 5.87), which denotes that participants did well on the aforementioned variables. Therefore, it failed to reject the null hypothesis.

Hypothesis

Null hypothesis (Ho): There is no significant difference between short-term memory and sounds exposed to classical music, white noise, brown noise, and ambient sounds in regards to memory concentration.

Alternative hypothesis (Ha): There is a significant difference between short-term memory and sounds exposed to classical music, white noise, brown noise, and ambient sounds in regards to memory concentration

Results Sections

To identify the differences between classical music, white noise, brown noise, and ambient sounds, we utilized the psytoolkit's primarily digit span task as an experiment to see and assess their cognitive performance and whether the aforementioned variables impact their memory concentration.

It was found that the data gathered showed no significant difference when four variables were employed. Supporting the idea of no significant difference, a repeated measures ANOVA was used to determine if there was a significant difference. Based on the assumption checks (Q-Q plot), post hoc tests (Tukey), and estimated marginal means, it holds up the idea that indeed, as mentioned, there is no significant difference.

There is strong evidence that participants who employed brown noise as their variable while undergoing the digit span task were efficient when tied to its mean (mean = 6.00). It means that most participants performed incredibly well when listening to brown noise.

As for classical music (mean = 5.73), white noise (mean = 5.80), and ambient sound (mean = 5.87), it is notable that participants also performed well, although not as superbly as brown noise. Even if classical music were the last to make brown noise, that doesn't mean it's a negative result. It only means that most participants just performed better when brown noise was utilized as their variable if a cognitive task was needed.

Interestingly, while the participants were taking the series of tests, the researchers observed that one particular respondent scored perfect, with 9 as the highest possible score on the test, which can also be deduced. Although brown noise was deemed to be the best variable for cognitive performance, other variables, like white noise, can be efficient for some people.

Comparing these four results from the variables used, it's undeniable how these variables impact them, with no significant difference as mentioned above, although it's clear participants leaned on brown noise as their top choice. Nevertheless, all variables employed were efficient for the participants when linked to cognitive performance.

Overall, the experiment is notably visible in the participant's performance in the digit span task while listening to the four variables. This goes to show that no matter what variables they employ, it has no significant impact on their cognitive performance.