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Materials and Methods For the experiment, two instruments were used in order to test the accuracy and precision of the operators. In order to test for the accuracy of the operators, the red and blue micropipettors with its white and blue tip, made from polypropylene, respectively, were used to transfer 1000 mL of distilled water and the required volumes of bromophenol blue (uL) to the microcentrifuge tubes. One member only did the transfer of the set volumes of 0.5, 1.0, 1.5, 2.0 and 2.5 µL of Bromophenol blue and 1000 mL of distilled water. Once the liquid has been transferred to the microcentrifuge tube, it was then vortexed to mix the contents of the tube until the dye immersed in the solution. After the tubes have been prepared, the spectrophotometer was warmed up and set to a wavelengthmeasured 540nm. With distilled water (blank solution), the spectrophotometer was set to zero. Once calibrated, the absorbance of the dye solutions was read by the spectrophotometer starting from the least concentrated to the most concentrated. In order to test for the precision of operators, again, the red and blue micropipettors, with its white and blue tips, respectively, were utilized to transfer the required volume of 2.5 µL to the microcentrifuge tubes. All the members took part in this process as the precision of each student in utilizing the micropipettor was taken into consideration for this portion of the experiment. Each member, using the blue micropipettor with its blue tip

transferred 1000 mL to the microcentrifuge tube, then afterwards, a volume of 2.5 µL of Bromophenol blue was placed in each of the five tubes. Once the solution has been prepared, the tubes were then vortexed in order to mix the contents of the tube and immerse the dye into the solution, the tube was placed to the microcentrifuge. After the tubes have been prepared, the tubes, together with the reagent blank was placed in the spectrophotometer, which read the absorbance of the dye solutions starting from the least concentrated to the most concentrated. Sample Preparation 1000 mL of distilled water was transferred to an empty microcentrifuge tube using the blue micropipettor and 0.5 µL of Bromophenol blue was transferred to the same microcentrifuge tube using the red micropipettor. Once the tube has been prepared, the tube was vortexed for 5 seconds to mix the contents of the solution. The spectrophotometer, set to the wavelength of 540 nm was calibrated and set to zero using the blank solution. Once calibrated, the absorbance of the tube containing water and Bromophenol blue was read.

Results and Discussion

Table 1. Data table of average absorbance (A) read per µL of Bromophenol blue The average absorbance read by the spectrophotometer per volume of Bromophenol blue per group were compared, and as the data table presents, it can be concluded that as more volume of Bromophenol blue is added, the absorbance read increases. As seen in table 1, the numbers marked red show an inconsistency with the results as the absorbance values read by the spectrophotometer is fluctuating thus providing an inaccurate and non-precise data. This can be seen in the data of group 5 and 6. A result of not properly mixing the Bromophenol blue or errors with transferring the right amount of colorant can account for the fluctuations with the absorbance levels, thus may result in the error of the data. As for group 1, the absorbance level of 0.013 A is very far from the absorbance level of 0.031 A yet only having a large difference with the amount of volume added, thus shows the non-precision of data taken. As for the numbers colored in purple, under group 3, the values highlighted show the most precise results our of all the 8 groups. As for accuracy, group 8, having the absorbance of 0.185 A, is the most accurate as its value is closest to to set absorbnce of 0.183 A. The succeeding linear graphs show the relationship between concentration of Bromophenol blue and absorbance (nm). Using the formula C1V1=C2V2, concentration 2 can be solved for. C1 is measured as (1.25% (g/w)/100) is multiplied to the volume of Bromophenol blue added to the

microcentrifuge tube (V1) then is divided by the total volume of distilled water and Bromophenol blue added to the microcentrifuge tube (V2), thus solving for C2. Once the x data (absorbance, nm) and y data (concentration, g/ µL) have been tabulated, the points were plotted in a linear graph. After plotting these points, a linear regression graph was drawn using the values of the slope (m), y intercept (b), and a. In order to generate a linear graph, the volume of Bromophenol blue was converted to concentration, as previously stated in order to show the linear relationship between concentration and absorbance. Thus, the linear equation is as follows, y=mx+b.

Figure 1. Linear Regression Graph of Absorbance x Concentration Figure 1 shows the linear regression graph of the absorbance x concentration.

It can be depicted from the graphs that there is a linear relationship between concentration and absorbance – such as an increase in absorbance (A) leads to an increase in concentration (g/ µL). This direct relationship can be explained using the Beer’s-Law. The Beer’s law can be represented by the formula A=ebc; a as the absorbance, b as the path length, e is the molar absorptivity or extinction component and c as the concentration. The linear graphs in figure 1 show linear relationship, as seen in the graphs of group 2, 3, 4 and 8. Group 1 and 7 shows linearity in its graph but as clearly shown, there is a portion in the graph which shows a number of outliers from the straight line

Asides measuring the slope, y intercept and a value using the x and y points, the correlation coefficient r, or the Pearson Product Moment Sample Coefficient of Correlation are also measured. As stated by Mendenhall et al (2012), this is the measure of strength of the linear relationship between two variables, and that the largest possible value for r is 1. The r values of groups 2,3,4 and 8 are also close to the correlation coefficient, 1, which means that the x and y points generated the best-fitting line, regression line, and shows the direct relationship of the two variables (concentration and absorbance). Group 1 and 7’s r values on the other hand are further from 1 due to the outliers in its regression line.

– thus any point not plotted in the linear line is called an outlier. Group 5 and 6 both show errors in its graph as group 5 made use of the volume values as its y values instead of the concentration of Bromophenol blue thus having a different graph among all other groups. As for group 6, a huge error has been made with the absorbance reading as there is a negative absorbance reading. Absorbance cannot be less than 0 and should not go beyond 1 – if absorbance does become negative or go beyond one, this is due to the wrong calibration of the spectrophotometer or a problem with the solution that is being read by the spectrophotometer.

With the data presented and the equations indicated per linear graph, it can be concluded that as concentration increases, the absorbance of the solution increases, and as the absorbance increases, the %T decreases as transmittance is the fraction of radiant energy that having entered a layer of absorbing material reaches it father boundary. Figure 2. Bar Graph showing the standard deviation of each student in relation to the average absorbance

Standard deviation determines how far a value (+/-) is from the mean (x) of its data set. Figure 2 illustrating the bar graph that shows the level of the average absorbance read by spectrophotometer per each student per group including the standard deviation from the mean or the average absorbance. The bars, on top of the cells represent the standard deviation from the mean. An accurate data would present only a small deviation, while a precise data will have “bars” almost the same length. It can be seen that the bars/lines representing the standard deviation in group 3, 4, 5, 6, 7 and 8 go beyond the “boundary” or range of the standard deviation. The usual accepted percent error is supposedly 10% but based on the interpretations, based on the computed standard deviations, it can be said that the percent error in most groups greatly exceed 10%; this of which is seen in the groups mentioned above. With the data presented in figure 2, it can be concluded that only group 1 and 2 were precise with their measured absorbance levels per student. Conclusion Data should be accurate and precise but it can be concluded that some groups were not precise in transferring the µL of Bromophenol blue and water to tube errors and had inaccurate results. For this reason, human errors and errors with the operators (such as in calibration) can be the reason why such errors occurred during the experiment. Fankhauser, D.B. (2007). Spectrophotomer use. Retrieved from: http://biology.clc.uc.edu/fankhauser/Labs/Microbiolog y/Growth_Curve/Spectrophotometer.htm

Friedl, S. (n.d). Evaluating data : precision, accuracy and error. Retrieved from: http://study.com/academy/lesson/evaluating-dataprecision-accuracy-error.html

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transferred 1000 mL to the microcentrifuge tube, then afterwards, a volume of 2.5 µL of Bromophenol blue was placed in each of the five tubes. Once the solution has been prepared, the tubes were then vortexed in order to mix the contents of the tube and immerse the dye into the solution, the tube was placed to the microcentrifuge. After the tubes have been prepared, the tubes, together with the reagent blank was placed in the spectrophotometer, which read the absorbance of the dye solutions starting from the least concentrated to the most concentrated. Sample Preparation 1000 mL of distilled water was transferred to an empty microcentrifuge tube using the blue micropipettor and 0.5 µL of Bromophenol blue was transferred to the same microcentrifuge tube using the red micropipettor. Once the tube has been prepared, the tube was vortexed for 5 seconds to mix the contents of the solution. The spectrophotometer, set to the wavelength of 540 nm was calibrated and set to zero using the blank solution. Once calibrated, the absorbance of the tube containing water and Bromophenol blue was read.

Results and Discussion

Table 1. Data table of average absorbance (A) read per µL of Bromophenol blue The average absorbance read by the spectrophotometer per volume of Bromophenol blue per group were compared, and as the data table presents, it can be concluded that as more volume of Bromophenol blue is added, the absorbance read increases. As seen in table 1, the numbers marked red show an inconsistency with the results as the absorbance values read by the spectrophotometer is fluctuating thus providing an inaccurate and non-precise data. This can be seen in the data of group 5 and 6. A result of not properly mixing the Bromophenol blue or errors with transferring the right amount of colorant can account for the fluctuations with the absorbance levels, thus may result in the error of the data. As for group 1, the absorbance level of 0.013 A is very far from the absorbance level of 0.031 A yet only having a large difference with the amount of volume added, thus shows the non-precision of data taken. As for the numbers colored in purple, under group 3, the values highlighted show the most precise results our of all the 8 groups. As for accuracy, group 8, having the absorbance of 0.185 A, is the most accurate as its value is closest to to set absorbnce of 0.183 A. The succeeding linear graphs show the relationship between concentration of Bromophenol blue and absorbance (nm). Using the formula C1V1=C2V2, concentration 2 can be solved for. C1 is measured as (1.25% (g/w)/100) is multiplied to the volume of Bromophenol blue added to the

microcentrifuge tube (V1) then is divided by the total volume of distilled water and Bromophenol blue added to the microcentrifuge tube (V2), thus solving for C2. Once the x data (absorbance, nm) and y data (concentration, g/ µL) have been tabulated, the points were plotted in a linear graph. After plotting these points, a linear regression graph was drawn using the values of the slope (m), y intercept (b), and a. In order to generate a linear graph, the volume of Bromophenol blue was converted to concentration, as previously stated in order to show the linear relationship between concentration and absorbance. Thus, the linear equation is as follows, y=mx+b.

Figure 1. Linear Regression Graph of Absorbance x Concentration Figure 1 shows the linear regression graph of the absorbance x concentration.

It can be depicted from the graphs that there is a linear relationship between concentration and absorbance – such as an increase in absorbance (A) leads to an increase in concentration (g/ µL). This direct relationship can be explained using the Beer’s-Law. The Beer’s law can be represented by the formula A=ebc; a as the absorbance, b as the path length, e is the molar absorptivity or extinction component and c as the concentration. The linear graphs in figure 1 show linear relationship, as seen in the graphs of group 2, 3, 4 and 8. Group 1 and 7 shows linearity in its graph but as clearly shown, there is a portion in the graph which shows a number of outliers from the straight line

Asides measuring the slope, y intercept and a value using the x and y points, the correlation coefficient r, or the Pearson Product Moment Sample Coefficient of Correlation are also measured. As stated by Mendenhall et al (2012), this is the measure of strength of the linear relationship between two variables, and that the largest possible value for r is 1. The r values of groups 2,3,4 and 8 are also close to the correlation coefficient, 1, which means that the x and y points generated the best-fitting line, regression line, and shows the direct relationship of the two variables (concentration and absorbance). Group 1 and 7’s r values on the other hand are further from 1 due to the outliers in its regression line.

– thus any point not plotted in the linear line is called an outlier. Group 5 and 6 both show errors in its graph as group 5 made use of the volume values as its y values instead of the concentration of Bromophenol blue thus having a different graph among all other groups. As for group 6, a huge error has been made with the absorbance reading as there is a negative absorbance reading. Absorbance cannot be less than 0 and should not go beyond 1 – if absorbance does become negative or go beyond one, this is due to the wrong calibration of the spectrophotometer or a problem with the solution that is being read by the spectrophotometer.

With the data presented and the equations indicated per linear graph, it can be concluded that as concentration increases, the absorbance of the solution increases, and as the absorbance increases, the %T decreases as transmittance is the fraction of radiant energy that having entered a layer of absorbing material reaches it father boundary. Figure 2. Bar Graph showing the standard deviation of each student in relation to the average absorbance

Standard deviation determines how far a value (+/-) is from the mean (x) of its data set. Figure 2 illustrating the bar graph that shows the level of the average absorbance read by spectrophotometer per each student per group including the standard deviation from the mean or the average absorbance. The bars, on top of the cells represent the standard deviation from the mean. An accurate data would present only a small deviation, while a precise data will have “bars” almost the same length. It can be seen that the bars/lines representing the standard deviation in group 3, 4, 5, 6, 7 and 8 go beyond the “boundary” or range of the standard deviation. The usual accepted percent error is supposedly 10% but based on the interpretations, based on the computed standard deviations, it can be said that the percent error in most groups greatly exceed 10%; this of which is seen in the groups mentioned above. With the data presented in figure 2, it can be concluded that only group 1 and 2 were precise with their measured absorbance levels per student. Conclusion Data should be accurate and precise but it can be concluded that some groups were not precise in transferring the µL of Bromophenol blue and water to tube errors and had inaccurate results. For this reason, human errors and errors with the operators (such as in calibration) can be the reason why such errors occurred during the experiment. Fankhauser, D.B. (2007). Spectrophotomer use. Retrieved from: http://biology.clc.uc.edu/fankhauser/Labs/Microbiolog y/Growth_Curve/Spectrophotometer.htm

Friedl, S. (n.d). Evaluating data : precision, accuracy and error. Retrieved from: http://study.com/academy/lesson/evaluating-dataprecision-accuracy-error.html

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