measurements and errors Flashcards
SI units
fundamental units
SI units made up of
mass - kg
length - m
time - secs
amount of substance - mol
temp - K
current - A
how to find SI units of force
F = ma
= kg x m/s
= kgm/s
larger prefixes
tera (T) 10^12
giga (G) 10^9
mega (M) 10^6
kilo (k) 10^3
smaller prefixes
centi (c) 10^-2
mili (m) 10^-3
micro (u) 10^-6
nano (n) 10^-9
pico (p) 10^-12
femto (f) 10^-15
random errors
affect precision - cause differences in measurements - causing spread around mean
CBAT VE REMOVED
how to reduce random errors
- 3 repeats + mean
- use computers/data loggers to enable smaller intervals and reduce human error
- use appropriate equipment eg micrometer not meter rule
systematic error
affect accuracy - occur due to faults in method or apparatus - cause results to be wrong by the same amount each time eg 2m too high
eg zero error, parallax error
reducing systematic error
- calibrate apparatus by measuring a know value eg a 1kg weight
- remove background radiation in radiation experiments
- read the meniscus at eye level
precision
how consistent the measurement are
repeatability
if the original experimenter can redo with the same method / equipment and get the same results
reproducibility
if the experiment is redone by a different person / technique / equipment- and same results are found its repeatable
resolution
the smallest change in quantity measured that gives a change in reading
accuracy
how close it is to the true value
uncertainty
bounds in which the accurate value is expected to lie
can be:
absolute
fractional
percentage
- to reduce fractional and percentage- measure larger quantities
reading vs measurement
- reading is where one value is found eg temp on a thermometer
- measurement is the difference between two readings eg length on a ruler
uncertainty in reading/ measurements
- uncertainty in a reading is +- half the smallest division
- in a measurement is +-the smallest division
digital readings - uncertainty
digital readings uncertainty is +- the last significant digit
repeated data uncertainty
+- half the range
eg mean +- range/2
reducing uncertainty
- fixing one end of a measurement
- measure multiple instances
(given to the same sig figs as the data)
adding / subtracting data and uncertainties
add absolute uncertainties
multiplying/ dividing data and uncertainties
add percentage uncertainty
(percentage uncertainty = uncertainty / value x 100)
raising data and uncertainties to a power
multiply % uncertainties by the power
uncertainty in a graph
error bars
like if best fit should go through all of them
uncertainty in a gradient
must go through ALL bars but you can draw the steepest and shallowest gradients (best and worst)
- uncertainty is the difference between the two/ best gradient x 100
estimation
approximate values of physical quantities in order to make comparisons or to check if a value they’ve calculated is reasonable
