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What is generally the BEST way to measure accuracy in a set of laboratory results?Group of answer choicesModeStandard deviationMedianMean

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What is generally the BEST way to measure accuracy in a set of laboratory results?Group of answer choicesModeStandard deviationMedianMean

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The best way to measure accuracy in a set of laboratory results is typically through the use of standard deviation. Standard deviation is a statistical measure that shows the extent of variation or dispersion of a set of values. A low standard deviation indicates that the values tend to be close to the mean (or expected value) of the set, while a high standard deviation indicates that the values are spread out over a wider range. This allows for a more precise understanding of how accurate the results are, as it provides information on the range of variation within the results.

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What is the best way to measure precision?Group of answer choicesModeStandard deviationMedianMean

Accuracy and PrecisionThe quality of experimental results can be categorised by two terms:Accuracy:  how closely the measured value of a quantity corresponds to its “true” or "accepted" value.Precision: the degree of reproducibility or agreement between repeated measurements.These two terms can be mutually exclusive (ie one term can occur irrespective of the outcome of the other term).  So the results could lay somewhere in amongst these four scenarios:accurate and precise,accurate and imprecise,inaccurate but precise, orinaccurate and imprecise. This is demonstrated graphically in the graphic to the right using targets.  The bullseye is the "true" value we are hoping to achieve. When the average of the results lands on (or around) the bullseye, we consider it an accurate result - this is represented by the top two targets.  Even though no results landed on the bullseye of the top-left target, on average, we are "hitting the bullseye" - if we increase the number of results, we will eventually hit the target.  However, because our results are imprecise, and there is a  large area this shot could land, we would not be confident on predicting when this event will likely occur. The ability that we can consistently land in the same region of the target is known as a precise result - this is represented by the two targets on the right.  Even though the bottom-right target is clearly missing the bullseye (inaccurate), we are confident in the value we are consistently achieving.  If we increase the number of results, we would be confident in predicting the location our next shot will land.   Let's identify these scenarios in a laboratory environment.  Let's say there are four pH meters in the laboratory.  You test the pH of the first one by submerging the electrode in a certified pH 7.00 reference buffer (See image on to the left).  You rinse the electrode with deonised water and then re-submerge it in the pH 7.00 reference buffer again.  You repeat this 3 more times to get a set of 5 values for this pH meter.  You repeat this again with the other three pH meters to obtain a set of five pH readings per pH meter.  You get the following results below.  Select the answer as to whether the set of results for each pH meter was accurate and/or precise. pH meter #1: 7.00, 7.01, 7.00, 6.99, 6.99 pH meter #2: 7.00, 6.89, 6.98, 7.10, 7.03 pH meter #3: 6.60, 6.58, 6.60, 6.61, 6.62 pH meter #4: 7.64, 7.81, 7.52, 7.67, 7.92

Which of the following most align with being sources of measurement error?Group of answer choices

When you analyse and interpret your data, which of the following is a best practice?Group of answer choicesIgnoring a few cases because they are inconsistentLooking for other ways to explain differences in resultsTesting to see if your hypothesis is supportedUsing the most powerful statistics, so your results appear stronger

You should concentrate on method, significance and alternative explanations when you analyse your results.Group of answer choicesTrueFalse

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