**Analysis** We ended with a sample of 27 participants, the data from 10 participants was corrupted and cannot be analyzed. The mean and standard deviation of accuracy for tasks in the low demand queue were 0.84 and 0.16. For tasks in the high demand queue, mean and standard deviation were 0.85 and 0.17. We concluded that these differences were not significant after running a signed rank wilcoxon test and finding a p-value of 0.31. The first attached graph shows the distribution of the difference in accuracy between low and high demand queues. We performed a two-way ANOVA to test the effect on reaction time by the overall queue demand, and the individual switching of tasks. The means and standard deviations for the reaction times were 2226.34 and 413.22 in the low demand queue, and 2408.12 and 493.05 in the high demand queue. The residuals were normally distributed, with constant variance centered at zero. Plots to check these assumptions are attached. Our only significant effect was task switching (p=.00). Demand had a p-value of .06, and the p-value for the interaction was .13. The residuals were constant, normally distributed, and centered at zero. The magnitude of the switch effect is demonstrated in the attached means plot. The mean and standard deviation of low demand choice rate was 0.58 and 0.12. A wilcoxon test with a null hypothesis of no preference (median=0.50) was performed to prove the significance of observed favor of low demand in our sample. Our resulting p-value of .00 tells us that this or a more extreme preference for low demand can be expected from anyone our sample represents. In contrast to our results, the original study found significant results for each of the above tests. Their participants were more accurate in the low demand queue than the high demand queue. Their participants also had significantly faster reaction times in the low demand queue than the high demand queue. Both task switching and reaction time had significant effects in the ANOVA conducted by the original authors. There also was a significant interaction between those factors. Despite a difference in significance between the original study and our replication, similarity in our descriptive statistics suggests that had we successfully matched or succeeded our goal sample size, there may have been statistical significance. **Key for Spreadsheets** ***anonymized_spreadsheet*** loRacc: low demand queue, repeat trial, percent of accurate responses. loSacc: low demand queue, switch trial, percent of accurate responses. hiracc: high demand queue, repeat trial, percent of accurate responses. hiSacc: high demand queue, switch trial, percent of accurate responses. loRrt: low demand queue, repeat trial, reaction time. loSrt: low demand queue, switch trial, reaction time. hiRrt: high demand queue, repeat trial, reaction time. hiSrt: high demand queue, repeat trial, reaction time. lochoice: percentage of choices from the low demand queue. Each row is one participant. ***ANOVAspreadsheet*** dem: which queue, high or low? switch: did the task switch? rt: reaction time. Each row is one participant