scipy.stats.bayes_mvs (arr, alpha) function calculates mean , variance and standard deviation in a given Bayesian confidence interval.
Parameters:
arr: [array_like] The input data can be multidimensional but will be flattened before use.
alpha: Probability that the returned confidence interval contains the true parameter.Results: mean , variance and standard deviation in the given Bayesian confidence interval.
Code # 1: Work
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Output:
arr1: [[ 20, 2, 7, 1, 34], [50, 12, 12, 34, 4]]
arr2: [50, 12, 12, 34, 4]
Mean of array1: Mean (statistic = 17.6, minmax = (7.99212522273964, 27.207874777260358))
var of array1: Variance (statistic = 353.2, minmax = (146.13176149159307, 743.5537128176551))
std of array1: Std_dev (statistic = 18.136411760663574, minmax = (12.088497073316974, 27.26818132581737))
Mean of array2: Mean (statistic = 22.4, minmax = (16.090582413339323, 28.709417586660674)) var of array2: Variance (statistic = 725.6, minmax = (269.47585801746374, 754.8278687119639))
std of array2: Std_dev (statistic = 23.872262300862655, minmax = (16.415719844632576, 27.4764) >