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HOW SCIENCE WORKS:

HOW SCIENCE WORKS Some important definitions

Categoric variable:

Categoric variable Is one that is best described by a label (usually a word) eg blue or brown eyes

Discrete variable:

Discrete variable Is one that you can only describe in whole numbers eg the number of leaves on a plant

Ordered variable:

Ordered variable Is one where you can put the data into order, but not give it an actual number eg the height of plants compared to each other (short, medium, tall)

Continuous variable:

Continuous variable Is one that we measure. Therefore its value could be any number including whole numbers eg Temperature (as measured by a thermometer) 35.6 ° C, 38.2 ° C

Independent variable:

Independent variable Is the one that is changed or selected by the investigator

Dependent variable:

Dependent variable Is measured by you for each change in your independent variable eg the time it takes for a reaction to occur at different temperatures

Control variable:

Control variable All the variables that are kept constant (the same) so that your investigation is a fair test. If a control variable does change it will have an effect on the dependent variable

The basis for an investigation:

The basis for an investigation Observations when supported by scientific knowledge can be used to make a hypothesis. This can be the basis for a prediction. A prediction links an independent variable to a dependent variable. Other variables need to be controlled

Fair Test:

Fair Test Is one in which only the independent variable affects the dependent variable. All other variables are controlled

Accuracy:

Accuracy Accurate measurements are very close to the true value An accurate set of repeat readings will have a mean (average) close to the true value But it is not always possible to know what the true value is

Precision:

Precision If your repeated readings are closely grouped together then you have precision. But only if you are using a measuring instrument with the appropriate scale eg using a ruler with a millimetre scale will give greater precision than one with only a centimetre scale

Reliability:

Reliability If you repeat the test as many times as you can,(minimum of 3) in exactly the same way and obtain results that are grouped closely together, then they are reliable results.

Improving Reliability:

Improving Reliability Reliability can be improved by carrying out more repeats and calculating a new mean

Checking Reliability:

Checking Reliability If you compare your results with those of others who have done the same investigation and they are the same , then your results are likely to be reliable

Validity:

Validity Data are valid if changes in the dependent variable are solely due to changes in the independent variable (a fair test was carried out)

Warning:

Warning Just because your results show precision doesn’t mean they are accurate Why not?

Random Error:

Random Error Usually due to a poor measurement being made

Systematic Error:

Systematic Error A method was carried out consistently but an error was being repeated ie doing the same thing wrong each time!

Anomalies:

Anomalies Are results that are out of line . If they are due to random error then they should be discarded (rejected) and not included in any calculation of a mean Occasionally there may be a very interesting reason why an anomaly is so different, so always carefully consider before discarding

Sensitivity:

Sensitivity The sensitivity of an instrument refers to the smallest change in a value that it can record This determines the precision of your measurements