1. DESIGNING AN EXPERIMENT

2.  Scientific Inquiry – the process of gathering evidence about the natural world and giving explanations based on evidence. DESIGNING AN EXPERIMENT

3.  Pose Questions  Often times when we make observations, we question why or how certain things happen STEPS FOR DESIGNING AN EXPERIMENT

4.  Define the Problem  After posing your questions, you should choose one problem that can be tested STEPS FOR DESIGNING AN EXPERIMENT

5.  Develop a Hypothesis  A possible answer to a scientific question that can be tested STEPS FOR DESIGNING AN EXPERIMENT

6.  Experiment  Create a controlled experiment that follows reliable scientific principles to test a hypothesis and prevents experimental bias STEPS FOR DESIGNING AN EXPERIMENT

7.  Controlled experiment – a scientific experiment in which only one variable is changed at a time STEPS FOR DESIGNING AN EXPERIMENT

8.  Variables  Factors in an experiment that can change STEPS FOR DESIGNING AN EXPERIMENT

9.  Constant/ Controlled Variable  A factor or condition that stays the same in an experiment  Can be more than one thing STEPS FOR DESIGNING AN EXPERIMENT

10.  Independent Variable  The only factor or condition that is intentionally changed by an investigator in an experiment.  The factor you wish to test STEPS FOR DESIGNING AN EXPERIMENT

11.  Dependent Variable  A factor or condition that might be affected as a result of change in the independent variable.  Factor you measure to gather results STEPS FOR DESIGNING AN EXPERIMENT

12.  Experimental Bias – an error in the design of the experiment STEPS FOR DESIGNING AN EXPERIMENT

13.  Collect and Interpret Data  Before starting your experiment, determine what observations you will make and what data you will gather STEPS FOR DESIGNING AN EXPERIMENT

14.  Qualitative Observations/Data – use the 5 senses  Example: see, hear, smell, taste, feel  Quantitative Observations/Data – use numbers  Example: How much? How many? STEPS FOR DESIGNING AN EXPERIMENT

15.  Tools such as data tables, diagrams, graphs, and models can help you interpret data by revealing patterns or trends STEPS FOR DESIGNING AN EXPERIMENT

16.  Draw Conclusions  Conclusion – a summary of what you have learned from an experiment  A conclusion is unreliable if it comes from the results of one experiment – many trials are needed before a hypothesis can be accepted as true STEPS FOR DESIGNING AN EXPERIMENT

17.  A reasonable conclusion is based on data and evidence  Examine the data objectively to see if the results support or fail to support your hypothesis STEPS FOR DESIGNING AN EXPERIMENT

18.  Faulty reasoning, or experimental bias, occurs when the conclusion is not supported by the data STEPS FOR DESIGNING AN EXPERIMENT

19.  Hypotheses are valuable even when they are not supported by the data – they can lead to further investigation  When you detect faulty reasoning, you need to obtain additional information to determine whether the conclusion is valid or not STEPS FOR DESIGNING AN EXPERIMENT

20.  Overgeneralization - draw a conclusion based on too little data  When a conclusion about a whole class of things is based on very few samples 3 TYPES OF FAULTY REASONING/EXPERIMENTAL BIAS

21. Overgeneralization Example: “German Shepherds shed their fur, and Springer Spaniels shed their fur. Therefore, all dogs shed fur.” This is an overgeneralization. Two types of dogs shed, but some kinds of dogs do not shed, such as Poodles. 3 TYPES OF FAULTY REASONING/EXPERIMENTAL BIAS

22.  Illogical conclusion – making an inference that is not supported by data  Often indicate a cause-and-effect relationship that does not exist, based on coincidental events 3 TYPES OF FAULTY REASONING/EXPERIMENTAL BIAS

23. Illogical Conclusion Example: Suppose you break a mirror and then fall on your way to school, losing your homework. You conclude that “Breaking mirrors causes bad luck.” This is an illogical conclusion based on two unrelated incidents. 3 TYPES OF FAULTY REASONING/EXPERIMENTAL BIAS

24.  Personal Bias – basing conclusions on opinion rather than information  Can lead to conclusions that are actually contradicted by the data  Determine whether the author or speaker is trying to argue for a particular point of view 3 TYPES OF FAULTY REASONING/EXPERIMENTAL BIAS

25. Personal Bias Example: Your friend says, “I don’t like doing labs. Chemicals smell bad.” This is not a scientific statement; it is purely opinion. 3 TYPES OF FAULTY REASONING/EXPERIMENTAL BIAS

26.  Communicate  Scientists share their results with others through writing and speaking  When scientists share the results of their research, they describe their procedure and data so that others can repeat their experiment STEPS FOR DESIGNING AN EXPERIMENT