class_docstr: Symbolic expression for the probability.
  
  Examples
  ========
  
  >>> from sympy.stats import Probability, Normal
  >>> from sympy import Integral
  >>> X = Normal("X", 0, 1)
  >>> prob = Probability(X > 1)
  >>> prob
  Probability(X > 1)
  
  Integral representation:
  
  >>> prob.rewrite(Integral)
  Integral(sqrt(2)*exp(-_z**2/2)/(2*sqrt(pi)), (_z, 1, oo))
  
  Evaluation of the integral:
  
  >>> prob.evaluate_integral()
  sqrt(2)*(-sqrt(2)*sqrt(pi)*erf(sqrt(2)/2) + sqrt(2)*sqrt(pi))/(4*sqrt(pi))
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code: def __new__(cls, prob, condition=None, **kwargs):
      prob = _sympify(prob)
      if condition is None:
          obj = Expr.__new__(cls, prob)
      else:
          condition = _sympify(condition)
          obj = Expr.__new__(cls, prob, condition)
      obj._condition = condition
      return obj
  
imports: import itertools
  from sympy.concrete.summations import Sum
  from sympy.core.add import Add
  from sympy.core.expr import Expr
  from sympy.core.function import expand
  from sympy.core.mul import Mul
  from sympy.core.relational import Eq
  from sympy.core.singleton import S
  from sympy.core.symbol import Symbol
  from sympy.integrals.integrals import Integral
  from sympy.logic.boolalg import Not
  from sympy.core.parameters import global_parameters
  from sympy.core.sorting import default_sort_key
  from sympy.core.sympify import _sympify
  from sympy.core.relational import Relational
  from sympy.logic.boolalg import Boolean
  from sympy.stats import variance, covariance
  from sympy.stats.rv import RandomSymbol, pspace, dependent, given, sampling_E, RandomIndexedSymbol, is_random, PSpace, sampling_P, random_symbols
label_desc: Use image node_id 1 for calling the Probability obj's underlying member method code with example usage: obj.__new__(cls, prob, condition) and returns: obj