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added lab 0
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rcc02007 committed Aug 28, 2018
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362 changes: 340 additions & 22 deletions ME3263_lab-00.ipynb

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9 changes: 9 additions & 0 deletions README.md
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# Lab 0 - Statistics and the Student t-test

We use statistics to draw conclusions from limited data. No measurement is exact. Every measurement you make has two types of uncertainties, *systematic* and *random*. *Systematic* uncertainties come from faults in your assumptions or equipment.
*Random* uncertainties are associated with unpredictable (or unforeseen at the
time) experimental conditions. These can also be due to simplifications of your
model. Here are some examples for caliper measurements:

In theory, all uncertainies could be accounted for by factoring in all physics
in your readings. In reality, there is a diminishing return on investment
for this practice. So we use some statistical insights to draw conclusions.
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12 changes: 12 additions & 0 deletions pretty_plots.py
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import matplotlib.pyplot as plt
plt.rcParams.update({'font.size': 22})
plt.rcParams['lines.linewidth'] = 3
plt.rcParams['text.usetex'] = True
plt.rcParams['text.latex.unicode'] = True
plt.rcParams['text.latex.preamble'] = [
r'\usepackage{siunitx}', # I need upright \micro symbols, but you need...
r'\sisetup{detect-all}', # ...this to force siunitx to actually use your fonts
r'\usepackage{helvet}', # set the normal font here
r'\usepackage{sansmath}', # load up the sansmath so that math -> helvet
r'\sansmath' # <- tricky! -- gotta actually tell tex to use!
]
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