1. GCSE Biology Glossary of terms

2. Variables- things that vary/ change In any experiment there are three variables An input or independent variable An outcome or dependent variable Some control variables Some examples….

3. Example Aim- to find the affect of light intensity on transpiration (water loss) in a plant. Distance can be changed

4. Independent variable The thing you decide to change In this case the distance between lamp and potometer Distance can be changed

5. Dependent variable The variable which changes as a result of your independent variable (depends on it) It is what you measure In this case the rate of transpiration measured here by the distance marker moved/ time Distance can be changed

6. Control variables Control variables are the ones you keep the same to make it a fair test E.g. same power of bulb, same surface area of plant Distance can be changed

7. Tables Distance from lamp (cm) Rate of transpiration (mm/s) 1 st reading2 nd reading3 rd readingaverage Independent variable in 1 st column Dependent variable in subsequent columns Repeats increase reliability Units in headings only No control variables in tables…

8. Types of variables There are 4 types of variables which may be found in any experiment Categoric- variables with a work label Ordered- A type of Categoric variable that can be ranked. Continuous- variables with any numerical value Discrete – A type of continuous variable, only whole numbers can be used.

9. Taking measurements A good experiment will collect evidence which are accurate, precise, reliable, cover the correct range and are therefore valid

10. Accuracy How close to the true value the results are If shooting an arrow at a bull's-eye, this would be the measure of how close you are to the centre… Accurate equipment is likely to be very sensitive to small changes The most accurate arrow

11. Precision How consistent the readings are Precise equipment will have small increments (e.g. mm on a ruler rather than cm) Measurements can be v precise but inaccurate if far from true value.

13. Reliability This is data you can trust If someone else repeated your experiment they would get the same results You increase reliability by repeats

14. Range For continuous variables this is from lowest value to highest value An appropriate range will cover the changes to independent variables which will affect dependent. e.g. for transpiration exp From 0cm to 50 cm is appropriate From 300 cm to 1000 cm is innapropriate

15. Validity Valid data must be both reliable and relevant to the question being posed An experiment is only valid if there is limited error. When evaluating you need to make a final judgement on validity.

16. Errors These can reduce the validity of your evidence Random errors Systematic errors Zero errors

17. Random errors Errors that just pop up on one or two results Can cause anomalies (best seen on a graph) Can be due to human error, faulty equipment, faulty technique Repetition will reduce their effect

18. Systematic errors These cause all errors to be shifted on way or another from the true value. Anomalies cannot easily be seen you need to know the true value Can be due to incorrectly calibrated equipment or wrong technique (if you do it wrong the same way each time)

19. Zero Errors A type of systematic error. Equipment does not return to zero, so all results shifted from true value by the same amount.

20. More information AQA specification for full glossary www.physics4u.co.uk has more examples and explanationswww.physics4u.co.uk