Making sense of data Essay Example for Free

Making sense of data Essay This is due to the atoms of the metal gaining kinetic energy. As they move faster they collide with passing electrons, inhibiting their passage. This creates not only resistance, but also more heat as electrons try to get rid of their energy. Considering all factors, I think that the results still clearly portray that there is a positive correlation between the length of wire and resistance. The resistivity of the metal can be calculated by using RL=k Where: R is resistance L is length K is the constant of resistivity (The ability of a metal to conduct). To maximise accuracy, I will use the point closest to the line of best fit to calculate this value. RL=k 200. 7=k 14? m=k This figure is a very rough approximation due to the Inaccuracy of the equipment used. Experiment 2: Cross-sectional Area and Resistance The purpose of this experiment is to prove the relationship between cross-sectional area and resistance. As the cross-sectional area increases, the resistance should decrease. This should happen because there will be more room for the electrons to flow through the metal. There will be fewer collisions, thus less resistance. This experiment was conducted by using multiple strands of wire, side by side. In order to calculate the total cross-sectional area, the number of strands multiplied the cross-sectional area of one strand. Note: Where the AreOhms column says E, this refers to Exp or x10^-4 ect. Cross-Sectional Area (m ) Amps (mA) Volts(V) Ohms(? ) Area(m ) Ohms(? ) Inv 0The cross-sectional area of wire used was 3310 cm, and the length was 1m for every trial. Using data from the above table: Yet again the resistivity can be calculated, this time using the equation: R = ? L A Where: R is resistance ?  m A graph to show the relationship between 1/R and Cross-sectional Area The positive correlation illustrates the proportionality between 1/R and the cross sectional area. The straight line is due to 1/R being the inverse of R. Instead of the resistance decreasing as the area increases on the graph, it makes both axes increase. This makes it easier to extract trends and identify errors. Also the regression of plots can be calculated. The regression of this particular line is 9. 919. This implies that the results plotted are almost perfect, that being 1. This exemplifies that there is definitely a relationship between the cross-sectional area of wire and the resistance. I would imagine that the minute errors are systematic. Small miss-calibrations in the equipment could lead to such errors, and using analogue meters would definitely contribute to this Conclusion In conclusion, both experiments have proven the relationships between the dimensional properties and resistance of wire. In each experiment, the resistivity of the wire was calculated. As it is a constant, it should always be the same for that particular wire. However, the resultant values arent incredibly similar. This may be due to the fact that Nichrome is an impure metal. Composed of both Chrome and Nickel, it may be un-uniformly proportioned, thus giving a different resistance. I would consider the second value to be the most accurate due to the fact that the line of regression on the graph is very close to 1 (perfect). It is very evident that there was a much larger error margin for the first set of results which could also be due to` lack of accuracy when measuring lengths of wire. Calculating is a much more reliable method, as illustrated in the cross-sectional area experiment. If I were to improve the experiment, I would use digital meters, which will have a much higher resolution and accuracy. To further the integrity of my results I would ensure that all measurements are made accurate and exact. As Physics Making Sense of Data Coursework 1 Calvin Stewart 22/04/2002 Show preview only The above preview is unformatted text This student written piece of work is one of many that can be found in our GCSE Electricity and Magnetism section.