Without seeing your experiment and the actual thermistor, it's difficult to provide exact guidance on data techniques. However, if the thermistor is the NTC type, and you're using a standard linear voltage divider circuit, the general relationship between measured Voltage "V" (in volts) and measured Temperature "T" (in degKelvin) would likely be
approximately similar to:
:(1): \ \ \ \ V \ = \ V_{s} \frac {R} {R + R_{0}e^{C(T - T_{0})} }
where V
s is the Voltage Source (in volts) used in the divider circuit, R the Resistance (in ohms) across which you are measuring V in the divider circuit, R
0 the calibration resistance (in ohms) provided by the manufacturer, T
0 the Calibration Temperature (in deg
Kelvin) provided by the manufacturer, and C the Thermister Coefficient value provided by the manufacturer.
For {V
s= 10 volts}, {R = 1000 ohms}, {R
0 = 1000 ohms}, {T
0 = 300 degKelvin}, and a NEGATIVE Thermistor Coefficient {C=(-0.05)}, the graph of Voltage "V" (vertical axis, in volts) versus Temperature "T" (horizontal axis, in degKelvin) would be similar to:
http://img191.exs.cx/img191/6674/thermistorexp4zk.jpg
The above graph illustrates how you could display your data. On standard Linear-Linear scales, graph your measured Voltages (vertical axis, in volts) versus measured Temperatures (horizontal axis, in degKelvin). The graph should look like that above.
Now notice the "Linear Region" in the graph's center that's fairly straight like a line. That region is the best operating region for your thermistor because the relationship between "V" and "T" is almost a straight line. By drawing a "Best-Fit Line" thru that
center region and determining the straight line's equation, you'll have important information about your thermistor's operating characteristics. (Use standard algebra to determine the line's equation from 2 points read from the line's endpoints.) More information on NTC thermistors can be found in the following document. Good Luck!
http://www.thermometrics.com/assets/images/ntcnotes.pdf
Incidentally, methods to determine "Best-Fit Curves" for measured data are called "Regression" techniques. The following site describes and demonstrates some methods which you might find useful in the future. (Scroll all the way down the page for the interactive portion.)
http://www.arachnoid.com/polysolve/
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