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						Hadley Wickham
					
				
			
			
				
	
			
			
			
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							0eedd7a31a
						
					
				
				
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					a182d0bdec
				
			@@ -16,7 +16,7 @@ There are three parts to a model:
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    data, and `a_1` and `a_2` are parameters that can vary to capture 
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    different patterns.
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1.  Next, you generate a __fitted model__ by finding the the model from the 
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1.  Next, you generate a __fitted model__ by finding the model from the 
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    family that is the closest to your data. This takes the generic model 
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    family and makes it specific, like `y = 3 * x + 7` or `y = 9 * x ^ 2`.
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