This document defines key scientific concepts like observation, inference, hypotheses, qualitative and quantitative data, independent and dependent variables. It also discusses when to use bar graphs versus line graphs, with bar graphs used for discrete data that can be counted, and line graphs showing relationships over continuous data. Finally, it lists the components of a successful experiment, including running multiple trials with randomly selected subjects and a large sample size to reduce bias.

1. ObservationInformation gathered using the 5 senses

2. InferenceA Conclusion made on the basis of facts rather than on direct observations

3. HypothesisAn “educated statement” that is testable in the natural worldHypotheses are never “proven”They are “supported”Hypotheses are made to be rejected

4. Qualitative DataData Described by Certain QualitiesAdjectives

5. Quantitative DataData That Can Be Measured in Numbers

6. Independent VariableThe variable that the experimenter changes or manipulates

7. Dependent VariableThe variable that the experimenter measures

8. When to use a bar graphDiscrete data – each item is a whole and separate unit (cats and dogs)You can’t really have a cat and a half!!Compare sets of data

9. When to use a line graphGraphs most commonly used in sciencethey show a relationshipContinuous data – the points could theoretically be subdividedAdditional points are always possibleGraphing over time, temperature, weight

11. A Successful Experiment IncludesMultiple TrialsIf using subjects, they are chosen at randomLarge sample sizeTries to remove all bias