Your results are valid if you are measuring the actual thing you want to measure AND your results are accurate - Validity, Experiements where variables have been controlled except the variable being tested - Fair test, An accurate measurement is one in which the average of the repeated readings is close to what we know is the true value - Accuracy, Variables that can be put into categories of order e.g. small, medium, large - Variable categoric, The one we measure each time we change the independent. Its the results. We plot on the Y-axis - Dependent variable, Data which has been checked so it can be judged whether reliable or not - Evidence, Variable we measure, it may have numerical data e.g temperature - Continuous variable, Affects all the results. Taking more data and an average will not change it. Results will be inaccurate - Errors systematic, Could affect our results but it doesnt because we have kept it the same in each experiment - Control variable, Variables that can be categorized e.g. blue eyes, brown eyes - Categoric variable, A variable that can only be a whole number e.g. number of leaves on a tree - Variable- discrete, When all variables have been kept the same apart form the independent - Reliable,

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