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A hypothesis is an educated guess based on observation. We can use a hypothesis to generate predictions to test it. A theory summarizes a hypothesis or a group of hypotheses that have survived repeated testing.
In this exercise we will look at the relationship between the truth of a hypothesis and the success or failure of predictions based upon it. We will see that:
Step 1
Imagine that you try to turn your television on using the remote control, but the television doesn’t start. You formulate a hypothesis: the batteries in the remote control are flat. You use your hypothesis to generate a prediction: replacing the batteries will fix the problem. You test your hypothesis by replacing the batteries and trying to turn the television on again. If the television starts, your prediction was successful.
The reasoning fits this general pattern: If H then P; P therefore H (where H stands for 'hypothesis' and P stands for 'prediction').
Drag these boxes onto the workspace and make an analysis map that shows the 'If H then P; P therefore H' pattern of reasoning:
Drag this image onto the workspace to proceed. You must be using the inbuilt browser in Rationale 1.3 or later.
Now check your work against the model answer by dragging this thumbnail onto the workspace:
Step 2
If the television starts after you replace the batteries then your prediction is successful. Does this mean that your hypothesis is definitely true? No.
The success of your prediction doesn’t guarantee your hypothesis is true (although it should increase our confidence in it, especially if we test repeatedly in different ways, for example using a volt meter to test the battery charge).
For example, suppose that the original batteries were fine, but one was inserted around the wrong way - in changing them you inadvertently fixed the problem by putting the new batteries in the right way.
Drag these boxes onto the workspace to clarify the reasoning:
Now check your work against the model answer by dragging this thumbnail onto the workspace:
Step 3
If the television doesn't start after you replaced the batteries then your prediction has failed. Does this failure mean we should conclude that your hypothesis is certainly false? Again, the answer is no. Your hypothesis may be correct despite the failure of the prediction.
For example, it might be the case that there are actually two problems: the batteries are indeed flat, but maybe someone has also switched the television off at the power point.
Let's make an analysis map to clarify the reasoning using these boxes:
Now check your work against the model answer:
To learn more about the 'If P then Q; P therefore Q' pattern of reasoning, and for a deeper analysis of the problem in step 3 click here.
This material has been developed independently of the International Baccalaureate, which in no way endorses it.
© Austhink 2013. Rationale Exercises version 0.1, Jan-13
