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# Ive gotten the first two answers but anything else you can answer for me would be extremely helpful, thank

you

!!!(! − )! −1 Where xi is the individual trial data, is the average of the trial data, and N is the number of trials. The closer the standard deviation is to zero, the more precise the data. For example, if we were to calculate the standard deviation of our three temperatures from before (23.2oC, 23.4oC, 23.5oC), we would do it as follows: = = 23.2 − 23.367 ! + 23.4 − 23.367
3−1 ! + 23.5 − 23.367 ! = 0.153 where 23.367 is the average of 23.2, 23.4, and 23.5 (taken by adding all of the numbers together and dividing by the number of trials, in this case, 3). Since the standard deviation here is relatively low, the precision of the measurements is relatively high. In addition to looking at the precision of data, it is also useful to know the accuracy of your measurements. Accuracy refers to how close experimental data is to the theoretical (or accepted) value and is typically measured by percent error. Percent error is calculated as: − ℎ
% = × 100 ℎ The lower the percent error, the more accurate your data. For example, the density of water is accepted to be 1.00 g/mL; if an experimenter calculates it to be 0.97 g/mL, then the percent error would be: 0.97 − 1.00

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