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Accuracy
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An accurate
measurement is one which is close to the true value. |
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Calibration
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This involves
fixing known points and then marking a scale on a measuring instrument,
between these fixed points. |
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Data
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This refers to a
collection of measurements (quantitative data) or observations (qualitative data).
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For
example: Data can be
collected for the volume of a gas or the type of rubber. |
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Datum
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The singular
of data. |
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Error
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- random |
These cause
readings to be different from the true value. Random errors may be detected
and compensated for by taking a large number of readings and repeating readings. You can then eliminate anomalies and average results.
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For
example: Random
errors may be caused by human error, a faulty technique in taking the
measurements, or by faulty equipment. |
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Error
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-
systematic |
These cause
readings to be spread about some value other than the
true value; in other words, all the readings are shifted one way or the
other way from the true value.
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For
example: A systematic
error occurs when using a wrongly calibrated instrument. |
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Error
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- zero |
These are a
type of systematic error. They are caused by measuring
instruments that have a false zero. |
For
example: A zero error
occurs when the needle on an ammeter fails to return
to zero when no current flows, or when a top-pan balance shows a reading
when
there is nothing placed on the pan.
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Evidence
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This
comprises data which have been subjected to some form of
validation. It is possible to give a measure of importance to data
which has been validated when coming to an overall judgement. |
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Fair test
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A fair test
is one in which only the independent variable has been
allowed to affect the dependent variable.Care has to be taken to keep all but the independent and dependent variables constant. |
For
example: A fair test
can usually be achieved by keeping all other variables constant. |
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Precision
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The precision
of a measurement is determined by the limits of the
scale on the instrument being used. Precision is related to the
smallest scale division on the measuring instrument that you are using.
It may be the case that a set of precise measurements has very little
spread about the mean value.
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For example: using a ruler with a millimetre
scale on it to measure the thickness of
a book will give greater precision than using a ruler that is only marked
in
centimetres.
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Reliability and Repeatablity
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The results
of an investigation were considered 'reliable' by AQA if the results
could be repeated. After much discussion this term was replaced (quite rightly in my opinion) with repeatablity. If someone else can carry out your investigation and
get the same results as you, then your results are more likely to be reliable and therefore 'repeatability' and 'relilability are linked.
One way of checking reliability is to compare your results with those
of others and/or quoted values - you being able to repeat them is not enough.
The repeatability of data can be improved by carrying out
repeat measurements and calculating a mean.
If the spread of results about that mean is large then the presicion is poor (see above).
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True Value
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This is the
accurate value which would be found if the quantity could
be measured without any errors at all. |
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Validity
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Data is only
valid for use in coming to a conclusion if the measurements taken are
affected by a single independent variable only. Data is not valid if, for
example, a fair test is not carried out or
there is observer bias. |
For
example: In an
investigation to find the effect on the rate of a reaction when
the concentration of the acid is changed, it is important that concentration is the only independent variable. If, during the
investigation, the temperature also increased as you increased the concentration, this would also have an effect on your results and the data
would no longer be valid |
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Variables
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- categoric |
A categoric variable
has values which are described by labels.
When you present the result of an investigation like this, you should
not plot the results on a line graph; you must use a bar chart or pie
chart.
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For
example: If you
investigate the effect of acid on different metals, eg
copper, zinc and iron, the type of metal you are using is a categoric variable. |
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Variables
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-
continuous |
A continuous
variable is one which can have any numerical value. When you present the
result of an investigation like this you should use a line graph. |
For
example: If you
investigate the effect on the resistance of changing the length of
a wire, the length of a wire you are using is a continuous variable since
it could
have any length you choose.
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Variables
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- control |
A control
variable is one which may, in addition to the independent variable, affect
the outcome of the investigation. This means that you should keep these
variables constant; otherwise it may not be a fair test. If it is
impossible to keep it constant, you should at least monitor it; in this way
you will be able to see if it changes and you may be able to decide whether
it has affected the outcome of the experiment. |
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Variables
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-
dependent and
independent variables
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Often in
science we are looking at 'cause and effect'. You can think
of the independent variable as being the 'cause' and the dependent
variable as being the 'effect'. In other words, the dependent variable
is the thing that changes as a result of you changing something else. |
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Variables
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-
dependent |
The dependent
variable is the variable the value of which you measure for each and every change in the independent variable. |
You usually plot this on the Y-axis of a graph |
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Variables
|
-
independent
|
The
independent variable is the variable for which values are changed or
selected by the investigator. In other word, this is the thing that you
deliberately change to see what effect it has. |
You usually plot this on the X-axis of a graph |
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Variables
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- discrete
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You may
sometimes come across this term. It is a type of categoric variable whose values are restricted to whole numbers. In other words you cannot have a 'half' of one of these. |
For
example, the number
of carbon atoms in a chain.
(You can't have half an atom!)
------
At A-level you get discrete ionisation energies for electron jumps within atoms - these are not 'whole' numbers but are discrete (you can't have any values between them - but at GCSE the discrete means 'whole' |
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Variables
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- ordered
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You may
sometimes come across this term. It is a type of categoric variable that can be ranked.
|
For
example, the size of
marble chips could be described as large, medium or small. |
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