Measurement Uncertainties

1 / 30

# Measurement Uncertainties - PowerPoint PPT Presentation

Measurement Uncertainties. Physics 161 University Physics Lab I Fall 2007. Measurements. What do we do in this lab? Perfect Measurement Measurement Techniques Measuring Devices Measurement Range . Uncertainties. Types of Errors

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.

## PowerPoint Slideshow about 'Measurement Uncertainties' - missy

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

### Measurement Uncertainties

Physics 161

University Physics Lab I

Fall 2007

Measurements
• What do we do in this lab?
• Perfect Measurement
• Measurement Techniques
• Measuring Devices
• Measurement Range
Uncertainties
• Types of Errors
• Random Uncertainties: result from the randomness of measuring instruments. They can be dealt with by making repeated measurements and averaging. One can calculate the standard deviation of the data to estimate the uncertainty.
• Systematic Uncertainties: result from a flaw or limitation in the instrument or measurement technique. Systematic uncertainties will always have the same sign. For example, if a meter stick is too short, it will always produce results that are too long.
Uncertainty
• Difference between uncertainty and error.
• Blunder is not an experimental error!
• Calibration
Mean and STD
• Multiple Measurements
• Average
• Standard Deviation
Reporting a Value
• To report a single value for your measurement use Mean and Standard Deviation
• Measured value= mean of multiple measurements ± Standard Deviation
Expressing Results in terms of the number of σ
• In this course we will use σ to represent the uncertainty in a measurement no matter how that uncertainty is determined
• You are expected to express agreement or disagreement between experiment and the accepted value in terms of a multiple of σ.
• For example if a laboratory measurement the acceleration due to gravity resulted in g = 9.2 ± 0.2 m / s2 you would say that the results differed by 3σ from the accepted value and this is a major disagreement
• To calculate Nσ
Accuracy vs. Precision
• Accurate: means correct. An accurate measurement correctly reflects the size of the thing being measured.
• Precise: repeatable, reliable, getting the same measurement each time. A measurement can be precise but not accurate.
Accuracy vs. Precision
• Precision depends on Equipment
• A more precise measurement has a smaller σ.

9.4±0.7 m/s/s 9.5±0.1 m/s/s

• Accuracy depends on how close the measurement is to the predicted value.

9.4±0.7 m/s/s 9.5±0.1 m/s/s

• Which one is a better measurement?

9.4±0.7 m/s/s 9.5±0.1 m/s/s

Absolute and Percent Uncertainties (Errors)

If x = 99 m ± 5 m then the 5 m is referred to as an absolute uncertainty and the symbol σx (sigma) is used to refer to it. You may also need to calculate a percent uncertainty ( %σx):

Please do not write a percent uncertainty as a decimal ( 0.05) because the reader will not be able to distinguish it from an absolute uncertainty.

Propagation of Uncertainties withaddition or Subtraction

If z = x + y or z = x – y then the absolute uncertainty in z is given by

Example:

Propagation of Uncertainties withMultiplication or Division

If z = x y or z = x / y then the percent uncertainty in z is given by

Example
• Let x=4±.4 and y=9±.9 then
Special Functions
• z=sin(x) for x=0.90±0.03
• Sin(0.93)=0.80
• Sin(0.90)=0.78
• Sin(.87)=0.76
• Z=0.78±0.02
Least Square Fitting
• In many instances we would like to fit a number of data points in to a line.
• Ideally speaking the data points should be on a line; however, due to random and systematic errors they are shifted either up or down from their ideal points.
• Least squares is a statistical model that determines the slope and intercept for a line by minimizing the sum of the residuals.
Least Squares

Slope

Intercept

Percent Difference

Calculating the percent difference is a useful way to compare experimental results with the accepted value, but it is not a substitute for a real uncertainty estimate.

Example: Calculate the percent difference if a measurement of g resulted in 9.4 m / s2 .

Significant Figures