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The First Year Physics Laboratory
The first year laboratory component of PHYS
107/109/Sci1 takes advantage of unique features of doing physics
in a laboratory setting. Most importantly you will discover that
science is not simply a static body of concepts and mathematics,
but is based on empirical observation and experimentation. The
laboratory is not primarily motivated by the aim to teach particular
physics concepts or to reinforce what is taught in lectures and
tutorials. Instead, the goal is to leave you with skills and
attitudes that will be of value no matter what your later academic
path may be. You will learn how to make observations and measurements,
how to build models that fit those measurements, and derive meaning
from the success or failure of those models. You will also learn
a variety of technical skills including the use of particular
equipment, carrying out wellestablished techniques, keeping
thorough laboratory notes, a wide range of computer skills, statistical
methods and the ability to communicate results and ideas. This
environment beyond the textbook also brings in two key features
of the real world: measurement uncertainty and the complex mix
of phenomena that can often be taking place simultaneously in
an experiment.
Learning Goals
Making Measurements
Most fundamentally, you will learn how to
take measurements, something which embraces a range of skills
and attitudes in addition to learning how to use specific equipment
and procedures. The emphasis will be on the most broadly applicable
skills. At the end of Phys 107/109/SciOne, you will be able to:
 identify the variables that might control
the phenomenon being studied in an experimental situation
 control experimental variables during an
experiment
 define:
 mean
 standard deviation
 experimental/systematic uncertainty
 statistical uncertainty
 assign appropriate dimensional units to all
measured quantities
 determine the precision of a measurement
 attach an experimental uncertainty to any
measured value, including:
 estimating uncertainty by studying distributions
in the data
 calculating uncertainty for the special case of a Poisson
distribution
 determining uncertainty due to noise (e.g., in electronics)
 ascertaining uncertainty due to instrumental precision
 identify and categorize the sources of uncertainty
in a measurement
 design measurements that minimize the sources
of uncertainty
 apply tactics for efficient data collection,
including:
 covering a wide variable range quickly, when possible
 evaluating data early and adjusting choices 'onthefly'
 evaluating whether or not magnitudes, units, and precision
of results are reasonable
Modelling Data
You will also learn an essential step in the
association of empirical measurements with theory, which is modelling
data. This includes building an awareness of how data sets can
differ from one another, the acquisition of some technical skills,
and the ability to make connections between discrete data and
mathematical functions. At the end of Phys 107/109/SciOne, you
will be able to:
 define:
 linear growth
 exponential growth
 exponential decay
 power law behaviour
 power law scaling
 create a twodimensional scatter plot of
data on linear scales
 create a histogram
 provide a verbal description of any given
twodimensional scatter plot of data on linear scales
 linearize:
 exponential distributions, by using semilog plots
 power law distributions, by using loglog plots and power
law scaling
 extract meaning from the slope and intercept
of data which has been linearized
Statistics and Data
Furthermore, you will learn some of the basic
and proper statistical treatments of data and models. This includes
understanding how and when to apply certain calculations, and
also the development of your ability to make evaluations of your
data and models based on these calculations. At the end of Phys
107/109/SciOne, you will be able to:
 calculate:
 the mean of a data set
 the standard deviation of a data set
 the uncertainty in the mean of a data set
 weigh the relative importance of numbers
that have differing uncertainty
 recognize whether numbers with an associated
uncertainty are in agreement with one another or not
 calculate the reduced chi square statistic,
which entails:
 a weighted, linear leastsquares fit to a straight
line
 a weighted, nonlinear leastsquares fit to a model
 and, from each, extract meaning and numerical values
with uncertainties of the fit parameters
 calculate the uncertainty in slope of a linear
model
 judge whether or not a model fits a data
set
Higher Level Skills and Attitudes
Lastly, you will develop some beneficial habits
of the mind. These are metaskills that might be considered the
next level in your ability to handle an experiment. At the end
of Phys 107/109/SciOne, you will be able to:
 offer a plausible modification or further
tests when confronted by a disagreement with an expected model
 devise experiments to search for and correct
hidden systematic errors when confronted by a disagreement with
an expected model
 develop a new experiment that further tests
a successful model after having drawn a conclusion from an experiment
 write a concise summary of an experiment
