Key terms working scientifically



Key terms when working scientificallyA support document for teachersThis documents is aimed at supporting Science teachers implement key 'working scientifically' terms into their teaching and learning programs. It is imperative that students familiarise themselves with these concepts in the syllabus as they are often forgotten in favour of the content. These concepts are throughout Stages 4-6, with HSC Science courses and exams require a deep understanding of them.This document will specifically cover the following topics related to the 'Working Scientifically' outcomes/component of the Stage 4 and 5 Science syllabus and the 'Skills' outcomes components of the Stage 6 Science syllabus:AccuracyReliabilityValidityPrecisionThese concepts are introduced and discussed in Stage 4 and 5 within the Working Scientifically Skills of the Science 7-10 Syllabus. The HSC Science courses and exams require a deeper understanding of the terms which are introduced in the Skills outcomes components of the Stage 6 Science syllabusesAny syllabus material referenced in this document is copyright NSW Education Standards Authority (NESA) for and on behalf of the Crown in the right of the State of New South Wales.Accuracy"Conformity to truth”‘Accuracy’ in science can be used to describe things in two different ways.The definition derived from the Stage 4-5 Science Syllabus refers to 'accuracy/plausibility (of first hand sources)' and defines it as "Accuracy estimated taking into consideration the evident sources of error and the limitations of the instruments used in making the measurements.” ?In implementing the scientific term of 'accuracy' into teaching and learning, it is worth noting the two parts of the definition: Accuracy of a result or investigation which refers to comparison between the experimental result and the accepted value.Note that this is only applicable when there is a 'true' or accepted value e.g. the acceleration due to gravity on the surface of Earth is accepted to be around 9.8 m/s2. In this we could improve the accuracy of the results mainly through ensuring the elimination of all systematic errors (such as calibration errors).For example, Millikan's famous oil drop experiment used a slightly incorrect value for the viscosity of air. This lead to a systematic error throughout his whole investigation regarding the charge of electrons, making his final result inaccurate.Another example would be forgetting to 'tare' a scale before measuring reactants for an investigation. All subsequent results and findings would be inaccurate due to this systematic error in procedure.Accuracy associated with the inherent uncertainty in a measurement.A better word to use for this definition of accuracy is precision. Sometimes, texts use ‘accuracy’ as a synonym for ‘precision’. When doing so they are referring to the exactness of a measurement; relating to the degree of refinement in measurement or specification (precision is discussed in section 4). The reason for this, is that the 'true value' of any measurement is limited by the precision of the instrument measuring it.For example the 'true' length of a desk may be 90.534321 cm, but we can only measure this as accurately as the precision of the instrument allows. In other words by measuring more significant figures with a more precise instrument your get closer to the 'true' value.2. Reliability“Trustworthy, dependable”Students interact with reliability in the context of both first-hand data and secondary sources and data through Stages 4-6. There is nuance in understanding 'reliability' in these two contexts. 2.1. Reliability of first-hand dataThe Stage 4-5 Science syllabus define the reliability of first-hand data as "The degree to which repeated observation and/or measurements taken under identical circumstances will yield the same results."Reliability refers to the spread (or lack thereof) of data produced by an investigation. If the results from an investigation are consistently close to each other they are reliable - if you get exactly the same result each time you would have 'perfect' reliability. Reliability can be assessed by repeating an experiment and measuring the amount of variation between the results (see Section 2.3). Reliability can also be impacted by the precision, such as margin of error (by minimising the +/-), in experimental results (see Section 4). If experimental results has a large margin of error then the investigation will be less reproducible, hence making it less reliable.For example, in investigating the bounce height of a basketball when dropped from various heights, always measuring a bounce height of 45 cm when the ball is released from 90cm over 10 trials is reliable data. However, if the bounce heights vary significantly when dropped from 90 cm, the data is not as reliable. Additionally, if the drop heights were not precisely measured, this would lead to more variability in bounce height measurements, decreasing the reliability of the data.2.2 Reliability of secondary sources and dataIn terms of secondary sources, reliability refers to how 'trustworthy' the source is, usually presenting with credentials.For example the CSIRO website would be a more reliable source of information about cancer treatment than a privately owned and operated web page.Even though a source is reliable, this is not to say that all the data on the site is valid. The reliability of a source can be assessed by comparing it to several other sources.If students are given experimental results as secondary source data, you can similarly assess its reliability through how much the data is based on repeatability and repetition.2.3 Repetition and reliabilityOften these terms are mistaken as interchangeable. While repetition is not reliability, it has a role to play in determining and assessing reliability of an investigation. Repetition can increase the overall reliability of results - by reducing the effect of outliers your results become more reproducible and reliable. This essentially reduces the effect of random errors. Repetition also helps you assess and measure the reliability of an experimental procedure.For example, repeatedly measuring values for current when investigating Ohm's law and finding a mean would reduce the effects of outliers and random errors on the final result. This would allow an identical experiment carried out to yield similar final results.It would also be possible to measure and assess the reliability of the procedure by analysing the spread of the data around the trend line. The more the data is 'spread' the less reliable the investigation.When considering the term repetition in this context, replication is assumed. That is, each repetition occurs under identical conditions.3. Validity“Derived correctly from premises already accepted, sound, supported by actual fact”The Stage 4-5 Science syllabus provides a definition for the validity of first-hand data: "The extent to which the processes and resultant data measure what was intended."A valid experiment is one that fairly tests the hypothesis and/or aim. In a valid experiment:There are control variables (i.e. all variables are kept constant apart from those being investigated)There is an appropriate control (for investigations that require a control)systematic errors have been eliminated or accounted forrandom errors are reduced by taking the mean of multiple measurements. Taking this into account, valid experiments should be accurate and reliable.An investigation could produce reliable results but be invalid For example, in Milikan's famous oil drop experiment, Milikan consistently got the wrong value for the charge of the electron because he was working with the wrong coefficient of viscosity for air. His experiment was inaccurate (see section 1: Accuracy) and invalid, because the experimental procedure was unable to successfully accomplish his aim.An invalid experiment can be due to a lack of appropriate controls or not using controls.For example, if testing the effect of fertiliser on the height of corn plants, control variables will need to be pot size, soil amount, seed depth, amount of water, time of watering and amount of sunlight.An appropriate control for the investigation would be a not using fertiliser.4. Precision"The degree of exactness with which a quantity is measured"As mentioned in section 1, precision is often used interchangeably with accuracy, however for clarity it is best to define them separately. As you can see from the below diagram, precision refers to the (lack of) spread of measurements or results.There are two ways that precision is used in Science:1. Precisions in instrumentsThe precision of a measuring device is limited by the finest division on its scale. More precise instruments are able to make measurements to more significant figures (see section 6).For example, a micrometer is more precise than a metre ruler and a digital thermometer is more precise than a bulb thermometer. Using a bulb thermometer to measure room temperature would yield less precise measurements when compared to a digital thermometer as it is difficult to calibrate.Note that a highly precise measurement is not necessarily an accurate one. ?As indicated in the first definition of accuracy (see Section 1), accuracy is the extent to which a measured value agrees with the "true" or accepted value for a quantity. ?In scientific experiments, we aim to obtain results that are both accurate and precise.2. Precision of results (+/-)The precision of a result is limited by the (random) error in and investigation (see Section 5). This means that results that have less 'percentage error' associated with them are considered more precise than results that have large 'percentage errors'.Consider experimental results of the heat of combustion for methane:Experiment 1: 55.2 ± 0.2 MJExperiment 2: 50.1 ± 0.5 MJExperiment 3: 53 ± 2 MJExperiment 1 has the smallest percentage error, and hence its results are considered more precise as there is the smallest amount of 'spread' around the results.Precision of results is therefore often related to the repeatability and reliability of an investigation or experiment. Measurements with large percentage errors represent an inability of getting consistent results and hence make the investigation unreliable. ................
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