@pytest.mark.parametrize('param_shapiro_pvalue, param_alpha, expected_result', [(10, 0.05, True), (0.01, 0.1, False), (0.0501, 0.05, True), (0.099, 0.1, False)])
def test_is_normal_distribution(self, param_shapiro_pvalue, param_alpha, expected_result):
    analytical_data = [[0.1, 0.2, 0.15]]
    concentration_data = [[0.2, 0.2, 0.3]]
    validator = LinearityValidator(analytical_data, concentration_data, param_alpha)
    validator.shapiro_pvalue = param_shapiro_pvalue
    assert (validator.is_normal_distribution is expected_result)
@pytest.mark.parametrize('param_shapiro_pvalue, param_alpha, expected_result', [(10, 0.05, True), (0.01, 0.1, False), (0.0501, 0.05, True), (0.099, 0.1, False)])
def test_is_normal_distribution(self, param_shapiro_pvalue, param_alpha, expected_result):
    analytical_data = [[0.1, 0.2, 0.15]]
    concentration_data = [[0.2, 0.2, 0.3]]
    validator = LinearityValidator(analytical_data, concentration_data, param_alpha)
    validator.shapiro_pvalue = param_shapiro_pvalue
    assert (validator.is_normal_distribution is expected_result)