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python_cookbook [2019/01/24 14:19] mantis [Logging to File] |
python_cookbook [2019/01/29 13:59] mantis [Spline Polynoms] |
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y = numpy.array([41.621207814814809, 42.328298238095236, 45.881729878787887, 43.800834224999996]) | y = numpy.array([41.621207814814809, 42.328298238095236, 45.881729878787887, 43.800834224999996]) | ||
y_smoothed = scipy.signal.cspline1d(y) | y_smoothed = scipy.signal.cspline1d(y) | ||
+ | </code> | ||
+ | |||
+ | ===== t-test ===== | ||
+ | |||
+ | <code python> | ||
+ | from scipy import stats | ||
+ | import numpy | ||
+ | import statistics | ||
+ | |||
+ | # http://www.biostathandbook.com/onesamplettest.html | ||
+ | data = [120.6, 116.4,117.2,118.1,114.1,116.9,113.3,121.1,116.9,117.0] | ||
+ | |||
+ | m = sum(data)/len(data) | ||
+ | |||
+ | null_hypothesis = 120 | ||
+ | |||
+ | t_value, p_value = stats.ttest_1samp(data, null_hypothesis) | ||
+ | |||
+ | print(statistics.stdev(data)) | ||
+ | print(numpy.std(data, ddof=1)) | ||
+ | |||
+ | print(t_value, p_value) | ||
</code> | </code> | ||
====== Statistical Functions ====== | ====== Statistical Functions ====== |