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PHYS 101 PREPARATION CLASS FOR PHYSICS LABORATORY

PHYS 101 PREPARATION CLASS FOR PHYSICS LABORATORY. DOĞUŞ ÜNİVERSİTESİ. OUTLINE. Significant Figure and Rounding Data Analysis Example : “Data Analysis for free fall ” Plotting graph Writing Conclusion. Significant Figure Rules.

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PHYS 101 PREPARATION CLASS FOR PHYSICS LABORATORY

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  1. PHYS 101 PREPARATION CLASS FOR PHYSICS LABORATORY DOĞUŞ ÜNİVERSİTESİ

  2. OUTLINE • SignificantFigureandRounding • Data Analysis • Example: “Data Analysisforfreefall” • Plottinggraph • WritingConclusion

  3. SignificantFigureRules • Thenumber of significantfigures in a quantity is thenumber of trustworthy • figures in it, thelastsignificantdigit in a measurement is somewhatuncertain • (but stilluseful), because it is basedupon an estimation • Allnon-zerodigitsconsideredsignificant • Zerosappearinganywherebetweentwonon-zerodigitsaresignificant

  4. Zero is accepted as a significantfigureifthere is a significantfigurebefore it. • Ifzerocomesbeforethenon-zerointeger • Ifzerocomesafterthenon-zerointeger

  5. Examples:

  6. OperationswithSignificantFigures • Inadditionorsubtraction, theresult can be as precise as thequantitywiththelowestprecision in theoperation. Resultmayhave a differentnumber of significantfiguresthantheinputs. • Whenwe do multiplicationordivision, thenumber of significantfigures of theobtainedresultshould be same as theonewiththeleastsignificantfigures in theoperation. Resultwithcorrect SF 165.4 140.8 1876. 12.49

  7. Rounding • A number is rounded off to the desired number of significant figures by dropping one or more digits to the right. • When the first digit dropped is equal to or more than 5, we add 1to the last digit retained. • When it is less than 5, the last digit retained does not change

  8. FREE FALL Freefallformulas t0 =0 t1 =0.88 s t2 =1.28 s t3 =1.63 s t4=2.18 s t5=2.31 s

  9. FreeFall: Experimental Data

  10. ScalingtheAxes GraphPaper PlottingtheaxesandWritingtheirNames & Units

  11. Plotting Data Best Fit

  12. Slope Of TheGraph Slope

  13. Analysis Slope Percentage of ErrorCalculation

  14. RandomErrors • A random error, as the name suggests, is random in nature and very difficult to predict. It occurs because there are a very large number of parameters beyond the control of the experimenter that may interfere with the results of the experiment. • Example:You measure the mass of a ring three times using the same balance and get slightly different values: 17.46 g, 17.42 g, 17.44 g

  15. Howto minimize randomerrors • Take more data. Random errors can be evaluated through statistical analysis and can be reduced by averaging over a large number of observations.

  16. SystematicErrors • Systematic error is a type of error that deviates by a fixed amount from the true value ofmeasurement. • All measurements are prone to systematic errors, often of several different types. • Sources of systematic error may be imperfect calibration of measurement instruments, changes in the environment which interfere with the measurement process and sometimes imperfect methods of observation The cloth tape measure that you use to measure the length of an object had been stretched out from years of use. (As a result, all of yourprevious length measurements would be smaller thantherecentone.) The electronic scale you use reads 0.05 g too high for all your mass measurements (because it is improperly tared throughout your experiment).

  17. Howto minimize systematicErrors? • Systematic errors are difficult to detect and cannot be analyzed statistically, because all the data is off in the same direction (either high or low). • You can not fixsystematicerrorbyrepeatingtheexperiment. • Systematic error can be located and minimized with careful analysis and design of the test conditions and procedure; by comparing your results to other results obtained independently, using different equipment or technique • Or by trying out an experimental procedure on a known reference value, and adjusting the procedure until the desired result is obtained (this is called calibration). 

  18. ConclusionPart • Conclusion is an importantpart of a laboratoryreport. Themainpurpose of theconclusionsection is tocomment on theresultsmentioned in thelabreportso it requiresmostcriticalthinking. • Youshouldshowwhetheryourresultsare in agreementwiththetheoraticalvalues. If not, thenyoushoulddiscussthepossiblereasonsfortheobserveddeviationfromthetheoreticalexpectations.

  19. ConclusionPart • Whenwritingyourconcluison; • Firstly, restatethepurpose of theexperiment. • Discussthesignificance of theexperiment, thinkaboutwhatyoulearned • You can link theresultstowhatyouread in theliterature, revieworothersourcesmentioned in theintroduction. • Do not writeprocedure as yourconclusion! • Suggestbiasesthatmayhaveaffectedtheexperimentaldesign;forinstance, randomandsystematicerrors. Discusshowthey can be eliminated in thefuture. Suggest any changes that can be made to the experimental procedure and how these changes might affect the data received in the lab.

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