can you write an ending statement The results found in this investigation can be said to be accurate and reliable because the data does not have any anomalous results and the standard deviation and the standard errors were relatively low when the mean value of different nuts are compared. The error bars were relatively short and some of them were overlapping; but that might be a cause of errors during data collection and random errors during the experiment.

Suggest one possible source of systematic error in the investigation.

During an experiment, your results do not support your hypothesis. What should you do next?

Which statement about systematic errors is not correct?A A systematic error can be caused by using an incorrectly calibrated instrument.B One particular type of systematic error can affect all the measurements by the same amount.C The effect of a systematic error can be reduced by repeating and averaging themeasurements.D Zero error is a type of systematic error

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

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. Group of answer choicespH meter #1: 7.00, 7.01, 7.00, 6.99, 6.99pH meter #2: 7.00, 6.89, 6.98, 7.10, 7.03pH meter #3: 6.60, 6.58, 6.60, 6.61, 6.62pH meter #4: 7.64, 7.81, 7.52, 7.67, 7.92