Mdm Flashcards
Calibration.
Marking a scale on a measuring measuring instrument
Tais involves establishing the relationship between indications of a measuring instrument and standard or reference quantity values which must be applied. For eg placing a thermometer in melting ice to see whether it reads zero, in order to check it has been calibrated properly
Accuracy
A measurement is considered accurate if it is judged to be close to the true value
Data
Information either qualitative or quantitative that has been collected
Quantitative data
is information about quantities; that is, information that can be measured and written down with numbers. Some examples of quantitative data are your height, your shoe size, and the length of your fingernails
Qualitative data
is information about qualities; information that can’t actually be measured. Some examples of qualitative data are the softness of your skin, the grace with which you run, and the color of your eyes
Measurement error
The difference between the measured value and the true value
Anomaly
Values in a set of results which are judged not to be part of the variation caused by random uncertainty
Random error
These cause readings to be spread about the true value due to results varying in an unpredictable way from one measurement to the next
They are present when any measurement is made, and cannot be corrected. The effect of random errors can be reduced by making more measurements and calculating a mean
Systematic error
These cause readings to differ from the true value by a consistent amount each time a measurement is made.
Sources of systematic error can include the environment, methods of observation or instruments used.
Systematic errors cannot be dealt with by simple repeats. If a systematic error is suspected, the data collection should be repeated using a different technique or a different set of equipment, and the results compared.
Zero error
Any indication that a measuring system gives a false reading when the true value of a measured quantity is zero, eg the needle on an ammeter failing to return to zero when no current flows.
A zero error may result in a systematic uncertainty.
Evidence
Data which has been shown to be valid.
Fair test
A fair test is one in which only the independent variable has been allowed to affect the dependent variable.
Hypothesis k
A proposal intended to explain certain facts or observations.
Interval
The quantity between readings, eg a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.
Precision
Precise measurements are ones in which there is very little spread about the mean
value.
Precision depends only on the extent of random errors – it gives no indication of how close results are to the true value.
Prediction
A prediction is a statement suggesting what will happen in the future, based on observation, experience or a hypothesis.
Range
The maximum and minimum values of the independent or dependent variables; important in ensuring that any pattern is detected.
For example a range of distances may be quoted as either: “From 10cm to 50 cm”
or
“From 50 cm to 10 cm”
Repeatable
A measurement is repeatable if the original experimenter repeats the investigation using same method and equipment and obtains the same results.
Reproducible
A measurement is reproducible if the investigation is repeated by another person, or by using different equipment or techniques, and the same results are obtained.
Resolution j
This is the smallest change in the quantity being measured (input) of a measuring instrument that gives a perceptible change in the reading.
Sketch graph
A line graph, not necessarily on a grid, that shows the general shape of the relationship between two variables. It will not have any points plotted and although the axes should be labelled they may not be scaled.
True value
This is the value that would be obtained in an ideal measurement.
Uncertainty
The interval within which the true value can be expected to lie, with a given level of confidence or probability, eg “the temperature is 20 °C ± 2 °C, at a level of confidence of 95 %.
Validity
Suitability of the investigative procedure to answer the question being asked. For example, an investigation to find out if the rate of a chemical reaction depended upon the concentration of one of the reactants would not be a valid procedure if the temperature of the reactants was not controlled.
