1. Hwk take it out.
Put some on board.

2. Experimental Errors & Uncertainty

3. Objectives Understand sources of uncertainty where they come from.
Define precision, accuracy.
Understand sources of random & systematic errors.
Methods to minimize random & systematic errors.

4. Errors/Uncertainties
Mistakes Happen –but there are no small mistakes if you are a civil engineer.

5. Measure the thickness of your textbook with a ruler.
Is that the actual thickness?
What are sources of uncertainty?

6. There is some uncertainty in every measurement.
Why?
Limits of measuring device.
Experimental procedure/technique.
Nature of measurement (too difficult) eg. Speed of light.

7. No Way! This scale is wrong!
Experimental Errors There is always a difference between measured value & actual value. That is why we never use fractions to report a measurement!! Weight ≠ 220 1/2 lbs. Weight = lbs.
No Way! This scale is wrong!

8. Two types of errors/uncertainty: Random & Systematic
Random – measured values too high and too low. Measured values fall above & below actual.
Caused by fluctuations in temperature, poor reflexes on stopwatch, poor vision, vibrations while measuring, variation in wire thickness.

9. True or False: Doing more experimental trials will reduce random error?

10. Systematic Error – measured values fall consistently above or below actual values.
Examples:
Poor instrument calibration.
Clock runs too fast or slow.
Parallax error s.t.
Balance is above or below zero.
Zero offset error.

11. Will doing more trials help?
Only with random error.

12. How can we correct systematic error?
Instrument calibration
Better lab technique
Mathematical correction factor.

13. This graph shows which type of error? Why?
Mass
Volume

14. This graph shows which type of error? Why?
volume
mass m

15. Which of the following are examples of experimental error?
Misreading the scale on the pan balance.
Incorrectly calculating a value by using the wrong data.
Incorrectly transferring data from your notes into your lab report.

16. Accuracy & Precision should be reported with measurement
Accuracy – how close a measurement is to the actual/accepted value. Low systematic error. Measurement average near accepted value.
Precision – the agreement among a number of measurements. Low random error – tight grouping.

18. What would the graphs look like?

19. Graph Accuracy Precision
inaccurate, imprecise
Accurate, precise
Precise,
not accurate
Accurate, not precise
# measurements

20. Error bars show uncertainty on graphs
Error bars show uncertainty on graphs. Line or curve should touch all the bars.

21. In class precision & accuracy sheet & IB MC questions.
Hwk .Kerr pg 1 – 8. Do pg 2 #3. And pg 6 #4, #7. Show all work.