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Practical Science Vocab

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Practical Science Vocab

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1. Interval

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.The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.

2. Uncertainty

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.The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.

3. Random error

The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.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.The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.

4. Validity

The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.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.The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.

5. Continuous variable

These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.Continuous variables can have values (called a quantity) that can be given a magnitude either by counting (as in the case of the number of shrimp) or by measurement (eg light intensity - flow rate etc).

6. Anomalies

These are values in a set of results which are judged not to be part of the variation caused by random uncertainty.The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.

7. Reproducible

The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.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.The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.

8. Resolution

This is the smallest change in the quantity being measured (input) of a measuring instrument that gives a perceptible change in the reading. For example a digital thermometer reads 5.6oc. It has a resolution of 0.1°c.The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.

9. Precision

The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.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.The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.

10. 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.The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.

11. Categoric variable

These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.Categoric variables have values that are labels. For example names of plants or types of material.The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.

12. Valid conclusion

The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.A conclusion supported by valid data - obtained from an appropriate experimental design and based on sound reasoning.The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.

13. True value

The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.This is the value that would be obtained in an ideal measurement.

14. Dependent variable

The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.Dependent variable is the variable of which the value is measured for each and every change in the independent variable.The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.

15. Calibration

The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.Marking a scale on a measuring instrument. The relationship between a measuring instrument and standard or reference value is checked. For example placing a thermometer in melting ice to see whether it reads zero - in order to check if it has been calibrated correctly.The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.

16. Evidence

Data which has been shown to be valid.These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.

17. Independent variable

These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.Independent variable is the variable for which values are changed or selected by the investigator.The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.

18. Control variable

These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.Control variable is one which may - in addition to the independent variable - affect the outcome of the investigation and therefore has to be kept constant or at least monitored.

19. Data

The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.Information - either qualitative or quantitative - that has been collected.The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.

20. Repeatable

The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.A measurement is repeatable if the original experimenter repeats the investigation using same method and equipment and obtains the same results.The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.

21. Fair test

The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.A fair test is one in which only the independent variable has been allowed to affect the dependent variable.

22. Prediction

The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.A prediction is a statement suggesting what will happen in the future - based on observation - experience or a hypothesis.These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.

23. Measurement 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. Random errors 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 new mean.The difference between a measured value and the true value.The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.

24. Systematic error

The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.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.The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.

25. Hypothesis

These cause readings to be spread about the true value - due to results varying in an unpredictable way from one measurement to the next. Random errors 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 new mean.The interval within which the true value can be expected to lie - with a given level of confidence or probability. For example 'the temperature is 20 °c ± 2 °c - at a level of confidence of 95%'.A proposal intended to explain certain facts or observations.The quantity between readings. For example a set of 11 readings equally spaced over a distance of 1 metre would give an interval of 10 centimetres.

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