A Pearson correlation was conducted to test the relationship between age (M = 35.32, SD = 11.45) and education (M = 13.83 , SD = 2.60). There was a statistically significant relationship between the two variables, r (148) =.52, p < .001). The relationship was positive and strong. As age increased, education increased.

A Spearman correlation was conducted to test the relationship between phone use (Mdn = 3.27) and sleep (Mdn = 7.52). There was a statistically significant relationship between the two variables, p = -.65, p < .001. The relationship was negative and strong. As phone use increased, sleep decreased.

A Pearson correlation was conducted to test the relationship between age (M = 35.32, SD = 11.45) # and education (M = 13.83 , SD = 2.60). There was a statistically significant relationship between the two variables, r (148) =.52, p < .001) #The relationship was positive and strong. As age increased, education increased.

A Chi-Square Test of Independence was conducted to determine if there was an association between nationality and scholarship awarded. The results showed that there was an association between , χ²(1) = 81.30, p < .001. The association was strong (Cramer's V = .52).

A Chi-Square Goodness of Fit test was conducted to determine if there was a difference between the observed ice cream purchase frequencies and the expected frequencies (20% chocolate, 20% strawberry, 20% mango, and 40% vanilla). The results show that there was a difference between the observed and expected frequencies, χ²(3) = 41.60, p < .001. The difference was moderate (Cohen's W = 0.41).

Phone Use and Sleep Correlation

Age and Education Correlation

Age and Education