A measurement result is considered accurate if it is close to the true value. (The true value is the value that would be obtained in an ideal measurement.)
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Calibration
Marking a scale on a measuring instrument. For example, placing a thermometer in melting ice to see if it reads zero. If it does, it has been calibrated correctly. This makes data more accurate.
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Data
Information that has been collected.
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Anomalies
Caused by random uncertainty. You should investigate them and try to work out what happened. If you can work out what happened, e.g. you measured something totally wrong, you can ignore them when processing your results.
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Measurement error
The difference between a measured value and a true value.
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Random error
This is when results vary in an unpredictable way from one measurement to the next. (The effect of random errors can be reduced by making more measurements and calculating a new mean)
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Systematic error
When the same error is made every time. For example, if you measured from the very end of your ruler instead of from the 0cm mark, all your measurements would be a bit small.
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Zero error
If a systematic error is caused by using equipment that isn't calibrated properly, it's called a zero error. For example, the needle on an ammeter failing to return to zero when no current flows.
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Evidence
Data which has been shown to be valid. (Valid means that the data is reliable (repeatable and reproducible) and answers the original question.)
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Fair test
A fair test is one in which only the independent variable (the one that you change) has been allowed to affect the dependent variable (the one that you measure.)
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Hypothesis
A proposal intended to explain certain facts or observations. The first step is to use the hypothesis to come up with a prediction.
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Interval
The quantity between readings, e.g. a set of 11 readings equally spaced over a distance of 1 metre would give an INTERVAL of 10 centimetres.
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Precision
Precise results are ones where data is all really close to the mean.
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Prediction
A prediction is a statement suggesting what will happen in the future, based on observation, experience or a hypothesis.
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Range
The maximum or minimum values of the independent or dependent variables. It is important in ensuring that any pattern is detected. For example, a range of distances may be quoted as either "From 10cm to 50cm" or "From 50cm to 10cm"
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Repeatable
A measurement is repeatable if the original experimenter repeats the investigation using the same method and equipment and obtains the same results.
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Resolution
The smallest change a measuring instrument can detect is called its resolution. E.g. some mass balances have a RESOLUTION of 1g, some have a resolution of 0.1g, and some are even more sensitive.
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Sketch graph
A line graph, not necessarily on a grid, which shows the general shape of the relationship between two variables. It will not have any points plotted and although the axis should be labelled they may not be scaled. (e.g. limiting factor graphs)
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True value
The value that would be obtained in an ideal measurement.
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Validility
SUITABILITY of the investigative procedure to answer the question being asked.
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Valid conclusion
A concusion supported by valid data obatined from an appropriate experimental design and based on sound reasoning
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Variables
Physical, chemical or biological QUANTITIES or CHARACTERISTICS.
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Categoric variable
A label. E.g. names of plants or types of material.
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Continuous variable
Variables given a magnitude either by counting or by measurement (e.g. light intensity, flow rate etc.)
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Control variable
The variable/s you KEEP THE SAME.
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Dependent variable
The variable you MEASURE.
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Independent variable
The variable you CHANGE.
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Other cards in this set
Card 2
Front
Marking a scale on a measuring instrument. For example, placing a thermometer in melting ice to see if it reads zero. If it does, it has been calibrated correctly. This makes data more accurate.
Back
Calibration
Card 3
Front
Information that has been collected.
Back
Card 4
Front
Caused by random uncertainty. You should investigate them and try to work out what happened. If you can work out what happened, e.g. you measured something totally wrong, you can ignore them when processing your results.
Back
Card 5
Front
The difference between a measured value and a true value.
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