Systematic vs Random Errors or Quality of Data

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The discussion centers on the impact of temperature on the resistance of copper wire and light bulbs during an experiment related to Ohm's Law. The increase in resistance due to heat is identified as a systematic error, as it consistently affects measurements in one direction, leading to uncertainty. It is noted that the change in resistance with temperature is not an inherent flaw but rather a characteristic of the materials involved. The quality of data is influenced by how measurements are taken and the conditions under which they are recorded. Understanding these factors is crucial for accurate evaluation in the context of the investigation.
Cruxxfay
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Both the copper wire and the light bulb became hotter and hotter when a current was constantly passing through them, resulting in an increase in their resistances, which in turn lowering the value of the current through the conductor. (I did not allow time for both the wire and the light bulb to cool down)

The question is, is this a systematic error or random error? Or does this flaw only affect the quality of the data?

I am doing this as my IA and this is part of my evaluation. I have to state which error this flaw causes. I generally think this is a systematic error because it causes an uncertainty in only one direction, but I am not quite sure.
This is an IA for Ohm's Law, to determine whether the copper wire and the light bulb obey Ohm's Law.
 
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The fact that resistance changes as a function of temperature is not an error or a flaw. I can assume you made many measurements of voltage and current--how you go about obtaining these data is usually where the errors and flaws creep in.
 
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