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Graph Analysis Discussion

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Discussion The graphs of the data presented that the percent coverage increased at a non-constant rate until reaching around optimal temperature (38.5°C) and decreased afterwards. The graphs also showed that the number of colonies initially increased to 25, but then decreased by 19 and then increased by 13. For both the number of colonies and percent coverage, there was no bacterial growth at 12°C. Consequently, there are no error bars because the percent coverage and colonial growth was always 0 at this temperature. Both trend lines are represented as polynomial curves. The equation for the graph comparing the number of colonies to temperature (y=.0025x3 - .2046x2 + 4.3706x) is an odd degree polynomial, meaning that the end behavior of …show more content…

Both tests show that when temperature changes from 12°C to 22°C, more Bacillus subtilis will grow. Between 12°C and 38.5°C, the growth of Bacillus subtilis increased, but the number of colonies decreased. Because the t-Stat value of percent coverage (13.95) is greater than the critical one-tail value (1.69), the null hypothesis should be rejected. Similarly, when performing a t-Test for bacterial colonies, the t-Stat value of 4.47 was greater than the one-tail critical value of 1.69, showing that at 38.5°C, there will be fewer colonies than at 12°C. However, as temperature increased, colony size did as well. Therefore, as temperature increased, so did the amount of Bacillus subtilis present. Based on the t-tests between 12°C and 49.5°C, it is determined that the percent coverage of bacteria increases whereas the number of colonies decreases. In the t-Test of the percentages of bacterial growth, the t-Stat value of 11.6 is larger than the critical value of 1.69, and in the t-Test of the number of colonies of Bacillus subtilis, the t-stat value of 8.90 is greater than the one-tail critical value of 1.69, presenting that the null hypothesis should be rejected in both cases. Although the number of colonies decreases, the size of the colonies increased as temperature did, further revealing that there is correlation between temperature change and

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