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April 14, 2023 16:06
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t-test of two distributions null vs alternative
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import seaborn as sns, numpy as np | |
from scipy import stats | |
import numpy as np | |
import statistics | |
Null_Hypothesis = "YieldA = YieldB" | |
Alternate_Hypothesis = "YieldA != YieldB" | |
Vx1_1 = [4618, 3094, 158, 4701, 2692, 2012, 2569, 1233, 1895, 181] | |
Vx2_1 = [3352, 174, 1661, 1984, 1518, 3594, 3346, 1834, 3300, 3816] | |
print("The r stat = ", r.statistic) | |
print("The r pvalue = ", r.pvalue) | |
print(r.statistic, r.pvalue) | |
A_mean_pts = statistics.mean(Vx1_1) | |
B_mean_pts = statistics.mean(Vx2_1) | |
print("Mean Points for A =", A_mean_pts) | |
print("Mean Points for B =", B_mean_pts) | |
tstat, pval = stats.ttest_ind(YieldA['pts'], 110) | |
print("The T Stat = %.2f, and the P Value = %.4f" % (tstat, pval)) | |
print("T Stat = %.2f, P Value = %.4f" % (tstat, pval)) | |
if pval < 0.03: | |
print("Reject the null hypothesis") | |
else: | |
print("Accept the null hypothesis") |
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