An independent-samples t-test was conducted to evaluate the hypothesis that using mental images produces a significant difference in memory performance. The group using mental images recalled more words (M = 25, SD = 4.71) than the group that did not use mental images (M = 19, SD = 4.22). This difference was significant, t(18) = -3.00, p < .05, two-tailed.

(Gravetter & Wallnau, 1996, p. 299).

We have carried out an independent-samples t-test to compare the happiness scores for American men and women. There was a significant difference in scores for men (M = 1.76, SD = .69) and women (M = 1.83, SD = .63), t(1502) = -2.20, p<.05, but the magnitude of the difference in the means was very small (eta squared = .003), with sex explaining only 0.3 per cent of the variance in happiness

(Dörnyei, 2007. p. 217)

Figure 1 shows the mean attractiveness ratings given by participants in each of the four experimental conditions: When participants were drunk, the attractiveness ratings were higher than when participants were sober, supporting the idea that the beer-goggles effect is alcohol dependent. The level of lighting appeared to have an effect in sober participants who rated the stooges as more attractive in dim lighting, M = 40.77, 95% CI [36.66, 44.77], than a light setting, M = 34.31, 95% CI [30.46, 38.65]; for drunk participants the differences between ratings in dim, M = 51.58, 95% CI [48.04, 55.00], and light, M = 55, 95% CI [51.15, 58.65], settings was less pronounced and in the opposite direction.

Figure 1. Graph showing the mean physical attractiveness ratings (and 95% confidence interval) given by participants when sober and drunk, and in dim and bright lighting.

A two-way 2 (alcohol: 0 pints or 6 pints) × 2 (lighting: dim vs. bright) repeated-measures ANOVA was conducted on the attractiveness ratings. This revealed a significant main effect of alcohol, F(1, 25) = 68.64, p < .001, ω2 = .34, indicating that attractiveness ratings were significantly higher when participants were sober. There was not a significant main effect of lighting, F(1, 25) = 0.50, p = .484, indicating that attractiveness ratings were similar overall in dim and bright conditions. The alcohol × lighting interaction was significant, F(1, 25) = 8.82, p = .006, ω2 = .21, indicating that difference in attractiveness ratings due to lighting was present in the sober participants but not the drunk ones.

(Field, 2016)

Mean sales for the organisation’s 30 employees were £46,600. As the mean, median and mode are virtually the same, this suggests these data are normally distributed. Consequently the standard deviation of 18.46 indicates that 95 per cent of sales fell within the range £10,318 to £82,682, the complete range being £68,000.

(Saunders & Lewis, 2012, p: 178)

There is a statistically significant strong positive relationship between the number of enquiries and the number of sales (r =.726, p < 0.001) and a statistically significant but weak to moderate relationship between the number of television advertisements and the number of enquiries (r =.362, p = 0.006). However, there is no statistically significant relationship between the number of television advertisements and the number of sales (r =.204, p = 0.131).

(Saunders, Lewis & Thornhill, 2012. p. 522)

The relationship between perceived control of internal states (as measured by the PCOISS) and perceived stress (as measured by the Perceived Stress Scale) was investigated using Pearson product-moment correlation coefficient. Preliminary analyses were performed to ensure no violation of the assumptions of normality, linearity and homoscedasticity. There was a strong, negative correlation between the two variables, r = -.58, n = 426, p < .0005, with high levels of perceived control associated with lower levels of perceived stress.

(Pallant, 2010, p. 135)

A set of Pearson correlations were computed to determine if there were any significant relationships between a number of employee variables. The correlation between starting and current salary is +.735; this is significant at the .01 level. The null hypothesis can be rejected. Starting salary appears to provide a moderate guide to current salary as it predicts around 54% of current salary level. The remainder of the unexplained variance may involve inter alia qualifications/skills developed over the time period and differential opportunities for promotion.
The correlation between current salary and age is +.354; this is significant at the .05 level and the null hypothesis can be rejected. This relationship is not strong with a coefficient of determination only of around 12.5%, suggesting the existence of a number of other factors that influence the relationship, such as skill level and experience. The correlation between age and absence is -.148; this is not significant and indicates a random relationship. There is no evidence to suggest that absence is more frequent at one age rather than another.

(Burns & Burns, 2008, p. 354)

A linear regression analysis was conducted to evaluate the prediction of monthly sales value from floor area of a set of 14 branches of a large multiple store. The scattergraph indicates that they are positively and strongly linearly related such that as floor area increases so does monthly sales income, in fact by $1,686 per sq mt. A histogram and residual plots indicate that linear regression assumptions are met.
The strong relationship between the two variables was reflected in an R² of +0.954 and adjusted R² of 0.902. Approximately 90% of the variance of monthly sales value was accounted for by its linear relationship with floor space. The overall regression was highly significant with F = 121.009, p > .001. The regression equation for predicting monthly sales value is: Predicted monthly sales value = 901.247 + 1.686 (floor area in sq mts).

(Burns & Burns, 2008, p. 384)

Hierarchical multiple regression was used to assess the ability of two control measures (Mastery Scale, Perceived Control of Internal States Scale: PCOISS) to predict levels of stress (Perceived Stress Scale), after controlling for the influence of social desirability and age. Preliminary analyses were conducted to ensure no violation of the assumptions of normality, linearity, multicollinearity and homoscedasticity. Age and social desirability were entered at Step 1, explaining 6% of the variance in perceived stress. After entry of the Mastery Scale and PCOISS Scale at Step 2 the total variance explained by the model as a whole was 47.4%, F(4, 421) = 94.78, p < .001. The two control measures explained an additional 42% of the variance in stress, after controlling for age and socially desirable responding, R squared change = .42, F change (2, 421) = 166.87, p < .001. In the final model, only the two control measures were statistically significant, with the Mastery Scale recording a higher beta value (beta = -.44, p < .001) than the PCOISS Scale (beta = -.33, p < .001).

(Pallant, 2010, p. 167)

A chi-square goodness-of-fit test indicates there was no significant difference in the proportion of smokers identified in the current sample (19.5%) as compared with the value of 20% that was obtained in a previous nationwide study, χ² (1, n = 436) = .07, p < .79.

(Pallant, 2010, p. 216)

A chi-square test for independence indicated no significant association between gender and smoking status, χ² (1, n = 436) = .34, p =.56, phi = -.03.

(Pallant, 2010, p. 222)

An independent-samples t-test was run to determine if there were differences in engagement to an advertisement between males and females. There were no outliers in the data, as assessed by inspection of a boxplot. Engagement scores for each level of gender were normally distributed, as assessed by Shapiro-Wilks test (p > .05). Homogeneity of variances was violated, as assessed by Levene’s Test for Equality of Variances (p = .013), so separate variances and the Welch-Satterthwaite correction were used. The advertisement was more engaging to male viewers (M = 5.56, SD = 0.35) than female viewers (M = 5.30, SD = 0.35), a statistically significant difference, M = 0.26, 95% CI (0.03, 0.48), t(37.998) = 2.325, p = .026.

An independent-samples t-test was conducted to compare the self-esteem scores for males and females. There was no significant difference in scores for males (M = 34.02, SD = 4.91) and females (M = 33.17, SD = 5.71; t (434) = 1.62, p = .11, two-tailed). The magnitude of the differences in the means (mean difference = .85, 95% 0: -1.80 to 1.87) was very small (eta squared = .006).

(Pallant, 2010, p. 243)

An independent-samples t-test was conducted to evaluate the hypothesis that smokers and non-smokers differ significantly in their self-concept levels. The mean self-concept score of non-smokers (M=46.61, sd = 11.17) was statistically significantly different (t = 21.579, df = 423.3, two-tailed p = .000) from that of smokers (M = 28.28, sd = 6.54). The effect size d = 2.09 implies a very strong effect.

(Burns & Burns , 2008. pp. 268-269)

We have carried out an independent-samples t-test to compare the happiness scores for American men and women. There was a significant difference in scores for men (M = 1.76, SD = .69) and women (M = 1.83, SD = .63), t(1502) = -2.20, p<.05, but the magnitude of the difference in the means was very small (eta squared = .003), with sex explaining only .3 per cent of the variance in happiness

(Dörnyei, 2007. p. 217)

The one-degree-of-freedom contrast of primary interest was significant at the specified p < .05 level, t(177) = 3.51, p < .001, d = 0.65, CI(0.35, 0.95).

(American Psychological Association, 2020, p. 182)

The Mann-Whitney U-test showed that there was no significant difference in absence rates in 2006 between male and female employees (U = 168.0, p = .413).

(Burns & Burns, 2008, p. 272)

A paired samples t test (N = 40) was conducted to evaluate whether there was a significant difference between initial and current salaries. The mean scores between initial and current salaries differed significantly (t = 17.385, df = 39, p < .000) with current salary having a significantly higher mean than the starting salon. The calculated effect size (d) was 2.75, indicating a large effect.

(Burns & Burns, 2008, p. 276)

A one-way analysis of variance indicated that there was a significant difference in happiness amongst white people (M = 1.77, SD = .60), black people (M = 1.97, SD = .65) and other races (M = 1.94, SD = .67), F (2, 1501) = 10.23, p < .001. The effect size was small (eta squared = .013). S-N-K post hoc tests showed that white people were significantly happier than members of the non-white races (black and other), p < .05, whereas the latter two groups did not differ from each other significantly.

(Dörnyei, 2007, p. 221)

A one-way between-groups analysis of variance was conducted to explore the impact of age on levels of optimism, as measured by the Life Orientation Test (LOT). Participants were divided into three groups according to their age (Group 1: 29yrs or less; Group 2: 30 to 44yrs; Group 3: 45yrs and above). There was a statistically significant difference at the p < .05 level in LOT scores for the three age groups: F (2, 432) = 4.6, p = .01. Despite reaching statistical significance, the actual difference in mean scores between the groups was quite small. The effect size, calculated using eta squared, was .02. Post-hoc comparisons using the Tukey HSD test indicated that the mean score for Group 1 (M = 21.36, SD = 4.55) was significantly different from Group 3 (M = 22.96, SD = 4.49). Group 2 (M = 22.10, SD = 4.15) did not differ significantly from either Group 1 or 3.

(Pallant, 2010, p. 255)

We have carried out an independent-samples t-test to compare the happiness scores for American men and women. There was a significant difference in scores for men (M = 1.76, SD = .69) and women (M = 1.83, SD = .63), t(1502) = -2.20, p<.05, but the magnitude of the difference in the means was very small (eta squared = .003), with sex explaining only 0.3 per cent of the variance in happiness

(Dörnyei, 2007. p. 217)

An independent-samples t-test was conducted to evaluate the hypothesis that smokers and non-smokers differ significantly in their self-concept levels. The mean self-concept score of non-smokers (M=46.61, sd = 11.17) was statistically significantly different (t = 21.579, df = 423.3, two-tailed p = .000) from that of smokers (M = 28.28, sd = 6.54). The effect size d = 2.09 implies a very strong effect.

(Burns & Burns , 2008. pp. 268-269)

A paired samples t test (N = 40) was conducted to evaluate whether there was a significant difference between initial and current salaries. The mean scores between initial and current salaries differed significantly (t = 17.385, df = 39, p < .000) with current salary having a significantly higher mean than the starting salon. The calculated effect size (d) was 2.75, indicating a large effect.

(Burns & Burns, 2008, p. 276)

A one-way analysis of variance indicated that there was a significant difference in happiness amongst white people (M = 1.77, SD = .60), black people (M = 1.97, SD = .65) and other races (M = 1.94, SD = .67), F (2, 1501) = 10.23, p < .001. The effect size was small (eta squared = .013). S-N-K post hoc tests showed that white people were significantly happier than members of the non-white races (black and other), p < .05, whereas the latter two groups did not differ from each other significantly.

(Dörnyei, 2007, p. 221)

A one-way between-groups analysis of variance was conducted to explore the impact of age on levels of optimism, as measured by the Life Orientation Test (LOT). Participants were divided into three groups according to their age (Group 1: 29yrs or less; Group 2: 30 to 44yrs; Group 3: 45yrs and above). There was a statistically significant difference at the p < .05 level in LOT scores for the three age groups: F (2, 432) = 4.6, p = .01. Despite reaching statistical significance, the actual difference in mean scores between the groups was quite small. The effect size, calculated using eta squared, was .02. Post-hoc comparisons using the Tukey HSD test indicated that the mean score for Group 1 (M = 21.36, SD = 4.55) was significantly different from Group 3 (M = 22.96, SD = 4.49). Group 2 (M = 22.10, SD = 4.15) did not differ significantly from either Group 1 or 3.

(Pallant, 2010, p. 255)

On average, participants reported that they took the evaluation process somewhat seriously (M = 6.81, SD = 2.78). However, on the forced choice question, only 20% of participants indicated that they took the evaluation process seriously all the time, and 4% of participants indicated that they never took the evaluation process seriously. The majority of participants (76%) indicated that they sometimes took the process seriously, but that at other times they just bubbled in answers in order to get done quickly.

Bassett, J., Cleveland, A., Acorn, D., Nix, M. & Snyder, T. (2015). Are they paying attention? Students’ lack of motivation and attention potentially threaten the utility of course evaluations. Assessment & Evaluation in Higher Education, 42, 431-442.

The analysis revealed reliably higher percentages of overlap when participants were required to cite three sources (M = 10.26%, SD = 5.66) than when citations were optional (M = 4.76%, SD = 7.30), F(1,85) = 8.35, p < .001, η².= .17. Contrary to expectation, all three participants who were identified by the researcher as having committed plagiarism were assigned papers that required citations. Finally, there was no significant interaction between warnings and assignment type, F(1,85) = .96, ns.

Youmans, R. J. (2011). Does the adoption of plagiarism-detection software in higher education reduce plagiarism? Studies in Higher Education, 36, 749–761.

There was a significant effect of condition upon self-reported disgust [interpersonal, M= 5.33, SD = 0.44; outgroup, M = 4.74, SD = 0.91; ingroup, M = 3.26, SD = 1.02, F(2, 42) = 25.09, p < 0.01, η² = 0.54]. As predicted, post hoc Tukey tests revealed that the disgust score was lower in the ingroup condition than in either the outgroup or interpersonal conditions (both p < 0.001) and that there was no significant difference between the interpersonal and outgroup conditions.

Reicher, S. D., Templeton, A., Neville, F., Ferrari, L. & Drury, J. (2015). Core disgust is attenuated by ingroup relations. Proceedings of the National Academy of Sciences of the United States of America, 113, 2631-2635.

Results indicate that laptop use by fellow students was the single most reported distracter (n = 229), accounting for 64% of all responses. This was significantly greater than all other responses combined (n = 130), χ² (1, N = 359) = 29.2, p < .001.

Fried, C. B. (2008). In-class laptop use and its effects on student learning. Computers & Education, 50, 906–914.

With respect to the effectiveness of annotation type, Table 1 shows that the Combination group consistently outperformed the other two groups across all measures. The Combination group did significantly better than the Text-only group for the Picture Recognition test: the effect size was .59, a medium effect according to Cohen (1988). The Combination group also outperformed the Picture-only group significantly for the Definition Supply test (strict): the effect size was .61 (a medium effect).

Yoshii, M. & Flaitz, J. (2002). Second language incidental vocabulary retention: The effect of text and picture annotation types. CALICO Journal, 20i>(1), 33-58.

In sex differences in human mate preferences conducted in 37 cultures, Buss (1989) reported that males value physical attractiveness in potential mate smore than females do in 34cultures (mean Cohen’s d=0.59).

Guéguen, N. (2015). High heels increase women’s attractiveness. Archives of Sexual Behavior, 44, 2227-2235

However, L2 writing score is not significantly correlated with LLAMA B, r = .05, LLAMA F, r = .09, and effect sizes for the correlation between L2 writing score and LLAMA total score, r =.23, LLAMA D, r = .13, as well as that between L2 writing score and productive vocabulary size, r = .23, are rather small.

Yang, Y, Sun, Y, Chang, P. & Li, Y. (2019). Exploring the relationship between language aptitude, vocabulary size, and EFL graduate students’ L2 writing performance. TESOL Quarterly, 3(3), 845-856.