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Welch's t-test: Difference between revisions
→{{header|Ruby}}: used corrections suggested by RuboCop
(added Ruby) |
(→{{header|Ruby}}: used corrections suggested by RuboCop) |
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Line 1,832:
=={{header|Ruby}}==
{{trans|Perl}}
<lang Ruby>def calculate_p_value(array1, array2)
return 1.0 if array1.size <= 1
return 1.0 if array2.size <= 1
Line 1,848 ⟶ 1,847:
end
return 1.0 if variance1 == 0.0 && variance2 == 0.0
welch_t_statistic = (mean1 - mean2) / Math.sqrt(variance1 / array1.size + variance2 / array2.size)
degrees_of_freedom = ((variance1 / array1.size + variance2 / array2.size)**2) /
a = degrees_of_freedom / 2
value = degrees_of_freedom / (welch_t_statistic**2 + degrees_of_freedom)
beta = Math.lgamma(a)[0] + 0.57236494292470009 - Math.lgamma(a + 0.5)[0]
acu = 10**
return value if a <= 0
return value if value < 0.0 || value > 1.0
return value if (value == 0)
psq = a + 0.5
cx = 1.0 - value
Line 1,869 ⟶ 1,868:
qq = a
indx = 1
xx = value
pp = a
qq = 0.5
indx = 0
# Soper reduction formula
rx = xx / cx
temp = qq - ai
term = term * temp * rx / (
#p "pp = #{pp}"▼
▲ value = value * Math.exp(pp * Math.log(xx) + (qq - 1.0) * Math.log(cx) - beta) / pp;
ns
if ns
rx =
▲ end
▲ #p "ai = #{ai}"
▲ psq = psq + 1.0
▲ end
▲ return value
end
d1 = [27.5, 21.0, 19.0, 23.6, 17.0, 17.9, 16.9, 20.1, 21.9, 22.6, 23.1, 19.6, 19.0, 21.7, 21.4]
d2 = [27.1, 22.0, 20.8, 23.4, 23.4, 23.5, 25.8, 22.0, 24.8, 20.2, 21.9, 22.1, 22.9, 20.5, 24.4]
d3 = [17.2, 20.9, 22.6, 18.1, 21.7, 21.4, 23.5, 24.2, 14.7, 21.8]
d4 = [21.5, 22.8, 21.0, 23.0, 21.6, 23.6, 22.5, 20.7, 23.4, 21.8, 20.7, 21.7, 21.5, 22.5, 23.6, 21.5, 22.5, 23.5, 21.5, 21.8]
d5 = [19.8, 20.4, 19.6, 17.8, 18.5, 18.9, 18.3, 18.9, 19.5, 22.0]
d6 = [28.2, 26.6, 20.1, 23.3, 25.2, 22.1, 17.7, 27.6, 20.6, 13.7, 23.2, 17.5, 20.6, 18.0, 23.9, 21.6, 24.3, 20.4, 24.0, 13.2]
d7 = [30.02, 29.99, 30.11, 29.97, 30.01, 29.99]
d8 = [29.89, 29.93, 29.72, 29.98, 30.02, 29.98]
x = [3.0, 4.0, 1.0, 2.1]
y = [490.2, 340.0, 433.9]
s1 = [1.0 / 15, 10.0 / 62.0]
s2 = [1.0 / 10, 2 / 50.0]
v1 = [0.010268, 0.000167, 0.000167]
v2 = [0.159258, 0.136278, 0.122389]
z1 = [9 / 23.0, 21 / 45.0, 0 / 38.0]
z2 = [0 / 44.0, 42 / 94.0, 0 / 22.0]
CORRECT_ANSWERS = [0.021378001462867, 0.148841696605327, 0.0359722710297968,
0.090773324285671, 0.0107515611497845, 0.00339907162713746, 0.52726574965384, 0.545266866977794].freeze
pvalue =
error = (pvalue - CORRECT_ANSWERS[0]).abs
printf("Test sets 1 p-value = %.14g\n", pvalue)
pvalue =
error += (pvalue - CORRECT_ANSWERS[1]).abs
printf("Test sets 2 p-value = %.14g\n", pvalue)
pvalue =
error += (pvalue - CORRECT_ANSWERS[2]).abs
printf("Test sets 3 p-value = %.14g\n", pvalue)
pvalue =
error += (pvalue - CORRECT_ANSWERS[3]).abs
printf("Test sets 4 p-value = %.14g\n", pvalue)
pvalue =
error += (pvalue - CORRECT_ANSWERS[4]).abs
printf("Test sets 5 p-value = %.14g\n", pvalue)
pvalue =
error += (pvalue - CORRECT_ANSWERS[5]).abs
printf("Test sets 6 p-value = %.14g\n", pvalue)
pvalue =
error += (pvalue - CORRECT_ANSWERS[6]).abs
printf("Test sets 7 p-value = %.14g\n", pvalue)
pvalue =
error += (pvalue - CORRECT_ANSWERS[7]).abs
printf("Test sets z p-value = %.14g\n", pvalue)
printf("the cumulative error is %g\n", error)
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