case_id,method_family,case_name,case_class,purpose,input_json,expected_kind,primary_engine,secondary_engine
OSCVB-001,descriptive_summary,typical,standard,Basic repeated integer data,"{""data"":[1,2,2,4,5]}",numeric_result,Hand formulas,NumPy
OSCVB-002,descriptive_summary,decimals,standard,Decimal values,"{""data"":[1.1,2.2,3.3,4.4]}",numeric_result,Hand formulas,NumPy
OSCVB-003,descriptive_summary,negative_mixed,standard,Negative and positive values,"{""data"":[-5,-1,0,2,8]}",numeric_result,Hand formulas,NumPy
OSCVB-004,descriptive_summary,single_value,boundary,Boundary n=1; sample variance intentionally undefined,"{""data"":[7]}",numeric_result,Hand formulas,NumPy
OSCVB-005,descriptive_summary,multimodal,standard,Multiple modes,"{""data"":[1,1,2,2,3]}",numeric_result,Hand formulas,NumPy
OSCVB-006,descriptive_summary,large_offset,stress,Large location with small spread,"{""data"":[1000000001,1000000002,1000000003]}",numeric_result,Hand formulas,NumPy
OSCVB-007,descriptive_summary,tiny_scale,stress,Very small scale,"{""data"":[1e-10,2e-10,3e-10,4e-10]}",numeric_result,Hand formulas,NumPy
OSCVB-008,descriptive_summary,zeros,boundary,Zero-heavy data,"{""data"":[0,0,0,1]}",numeric_result,Hand formulas,NumPy
OSCVB-009,descriptive_summary,invalid_empty,invalid,Empty data must be rejected,"{""data"":[]}",invalid_input,Hand formulas,NumPy
OSCVB-010,descriptive_summary,invalid_text,invalid,Nonnumeric entry must be rejected,"{""data"":[1,""abc"",3]}",invalid_input,Hand formulas,NumPy
OSCVB-011,standard_normal_probability,left_zero,boundary,Central probability,"{""mode"":""left"",""z"":0}",numeric_result,erf/erfc formula,SciPy norm
OSCVB-012,standard_normal_probability,right_196,standard,Common 5% two-sided threshold tail,"{""mode"":""right"",""z"":1.96}",numeric_result,erf/erfc formula,SciPy norm
OSCVB-013,standard_normal_probability,left_negative,standard,Negative z,"{""mode"":""left"",""z"":-1.645}",numeric_result,erf/erfc formula,SciPy norm
OSCVB-014,standard_normal_probability,between_one,boundary,Central interval,"{""mode"":""between"",""lower"":-1,""upper"":1}",numeric_result,erf/erfc formula,SciPy norm
OSCVB-015,standard_normal_probability,extreme_right,stress,Extreme upper tail,"{""mode"":""right"",""z"":8}",numeric_result,erf/erfc formula,SciPy norm
OSCVB-016,standard_normal_probability,extreme_left,stress,Extreme lower tail,"{""mode"":""left"",""z"":-8}",numeric_result,erf/erfc formula,SciPy norm
OSCVB-017,standard_normal_probability,small_z,standard,Rounding-sensitive near zero,"{""mode"":""left"",""z"":1e-06}",numeric_result,erf/erfc formula,SciPy norm
OSCVB-018,standard_normal_probability,wide_between,standard,Near-total probability,"{""mode"":""between"",""lower"":-6,""upper"":6}",numeric_result,erf/erfc formula,SciPy norm
OSCVB-019,standard_normal_probability,invalid_bounds,invalid,Reversed bounds must be rejected,"{""mode"":""between"",""lower"":2,""upper"":-2}",invalid_input,erf/erfc formula,SciPy norm
OSCVB-020,standard_normal_probability,invalid_text,invalid,Nonnumeric z must be rejected,"{""mode"":""left"",""z"":""abc""}",invalid_input,erf/erfc formula,SciPy norm
OSCVB-021,binomial_probability,exact_basic,standard,Symmetric exact probability,"{""n"":10,""p"":0.5,""mode"":""exact"",""x"":5}",numeric_result,Exact combinatorial sum,SciPy binom
OSCVB-022,binomial_probability,at_most,standard,Lower cumulative probability,"{""n"":20,""p"":0.3,""mode"":""at_most"",""x"":4}",numeric_result,Exact combinatorial sum,SciPy binom
OSCVB-023,binomial_probability,at_least,standard,Upper cumulative probability,"{""n"":20,""p"":0.3,""mode"":""at_least"",""x"":8}",numeric_result,Exact combinatorial sum,SciPy binom
OSCVB-024,binomial_probability,between,standard,Inclusive interval,"{""n"":30,""p"":0.6,""mode"":""between"",""lower"":15,""upper"":20}",numeric_result,Exact combinatorial sum,SciPy binom
OSCVB-025,binomial_probability,p_zero,boundary,Degenerate p=0 boundary,"{""n"":8,""p"":0.0,""mode"":""exact"",""x"":0}",numeric_result,Exact combinatorial sum,SciPy binom
OSCVB-026,binomial_probability,p_one,boundary,Degenerate p=1 boundary,"{""n"":8,""p"":1.0,""mode"":""at_least"",""x"":8}",numeric_result,Exact combinatorial sum,SciPy binom
OSCVB-027,binomial_probability,large_n,stress,"Large n, small p","{""n"":1000,""p"":0.01,""mode"":""at_most"",""x"":15}",numeric_result,Exact combinatorial sum,SciPy binom
OSCVB-028,binomial_probability,rare_event,stress,Rare-event upper probability,"{""n"":200,""p"":0.001,""mode"":""at_least"",""x"":2}",numeric_result,Exact combinatorial sum,SciPy binom
OSCVB-029,binomial_probability,invalid_p,invalid,"p outside [0,1]","{""n"":10,""p"":1.2,""mode"":""exact"",""x"":5}",invalid_input,Exact combinatorial sum,SciPy binom
OSCVB-030,binomial_probability,invalid_x,invalid,x greater than n,"{""n"":10,""p"":0.5,""mode"":""exact"",""x"":11}",invalid_input,Exact combinatorial sum,SciPy binom
OSCVB-031,one_sample_t,typical_two_sided,standard,Ordinary two-sided test,"{""data"":[12,15,14,10,13,16],""mu0"":11,""alternative"":""two-sided""}",numeric_result,Hand statistic + t distribution,SciPy ttest_1samp
OSCVB-032,one_sample_t,greater,standard,One-sided greater,"{""data"":[5.1,5.3,5.2,5.4,5.0],""mu0"":5,""alternative"":""greater""}",numeric_result,Hand statistic + t distribution,SciPy ttest_1samp
OSCVB-033,one_sample_t,less,standard,One-sided less,"{""data"":[8,7,9,6,8,7],""mu0"":9,""alternative"":""less""}",numeric_result,Hand statistic + t distribution,SciPy ttest_1samp
OSCVB-034,one_sample_t,n_two,boundary,Smallest valid sample,"{""data"":[1,3],""mu0"":0,""alternative"":""two-sided""}",numeric_result,Hand statistic + t distribution,SciPy ttest_1samp
OSCVB-035,one_sample_t,large_offset,stress,Large location,"{""data"":[1000001,1000002,1000003,1000004],""mu0"":1000000,""alternative"":""two-sided""}",numeric_result,Hand statistic + t distribution,SciPy ttest_1samp
OSCVB-036,one_sample_t,tiny_difference,stress,Rounding-sensitive difference,"{""data"":[1.000001,1.000002,0.999999,1.0],""mu0"":1,""alternative"":""two-sided""}",numeric_result,Hand statistic + t distribution,SciPy ttest_1samp
OSCVB-037,one_sample_t,negative,standard,Negative-valued sample,"{""data"":[-4,-2,-3,-5,-1],""mu0"":-2,""alternative"":""two-sided""}",numeric_result,Hand statistic + t distribution,SciPy ttest_1samp
OSCVB-038,one_sample_t,large_n,stress,Larger deterministic sample,"{""data"":[10.0,10.01,10.02,10.03,10.04,10.05,10.06,10.07,10.08,10.09,10.1,10.11,10.12,10.13,10.14,10.15,10.16,10.17,10.18,10.19,10.2,10.21,10.22,10.23,10.24,10.25,10.26,10.27,10.28,10.29,10.3,10.31,10.32,10.33,10.34,10.35,10.36,10.37,10.38,10.39,10.4,10.41,10.42,10.43,10.44,10.45,10.46,10.47,10.48,10.49,10.5,10.51,10.52,10.53,10.54,10.55,10.56,10.57,10.58,10.59,10.6,10.61,10.62,10.63,10.64,10.65,10.66,10.67,10.68,10.69,10.7,10.71,10.72,10.73,10.74,10.75,10.76,10.77,10.78,10.79,10.8,10.81,10.82,10.83,10.84,10.85,10.86,10.87,10.88,10.89,10.9,10.91,10.92,10.93,10.94,10.95,10.96,10.97,10.98,10.99],""mu0"":10.4,""alternative"":""two-sided""}",numeric_result,Hand statistic + t distribution,SciPy ttest_1samp
OSCVB-039,one_sample_t,invalid_n,invalid,n<2 must be rejected,"{""data"":[5],""mu0"":5,""alternative"":""two-sided""}",invalid_input,Hand statistic + t distribution,SciPy ttest_1samp
OSCVB-040,one_sample_t,invalid_zero_variance,invalid,Zero variance must be flagged,"{""data"":[3,3,3,3],""mu0"":2,""alternative"":""two-sided""}",invalid_input,Hand statistic + t distribution,SciPy ttest_1samp
OSCVB-041,independent_t_welch,typical,standard,Ordinary unequal-variance comparison,"{""group1"":[12,14,15,13,16],""group2"":[10,11,9,12,10],""alternative"":""two-sided""}",numeric_result,Welch formulas,SciPy ttest_ind
OSCVB-042,independent_t_welch,unequal_variance,standard,Strong variance inequality,"{""group1"":[1,2,3,4,20],""group2"":[5,5.2,5.1,4.9,5.0],""alternative"":""two-sided""}",numeric_result,Welch formulas,SciPy ttest_ind
OSCVB-043,independent_t_welch,greater,standard,One-sided greater,"{""group1"":[8,9,10,11,12],""group2"":[5,6,7,8,9],""alternative"":""greater""}",numeric_result,Welch formulas,SciPy ttest_ind
OSCVB-044,independent_t_welch,less,standard,One-sided less,"{""group1"":[1,2,3,4],""group2"":[3,4,5,6,7],""alternative"":""less""}",numeric_result,Welch formulas,SciPy ttest_ind
OSCVB-045,independent_t_welch,small_samples,standard,Two observations per group,"{""group1"":[1,4],""group2"":[2,3],""alternative"":""two-sided""}",numeric_result,Welch formulas,SciPy ttest_ind
OSCVB-046,independent_t_welch,large_offset,stress,Large location,"{""group1"":[1000001,1000002,1000004],""group2"":[1000000,1000001,1000001],""alternative"":""two-sided""}",numeric_result,Welch formulas,SciPy ttest_ind
OSCVB-047,independent_t_welch,negative,standard,Negative groups,"{""group1"":[-5,-4,-3,-2],""group2"":[-1,0,1,2],""alternative"":""two-sided""}",numeric_result,Welch formulas,SciPy ttest_ind
OSCVB-048,independent_t_welch,unbalanced,standard,Unequal sample sizes,"{""group1"":[1,2,3,4,5,6,7,8],""group2"":[2,4,6],""alternative"":""two-sided""}",numeric_result,Welch formulas,SciPy ttest_ind
OSCVB-049,independent_t_welch,invalid_n,invalid,Group with n<2,"{""group1"":[1],""group2"":[2,3],""alternative"":""two-sided""}",invalid_input,Welch formulas,SciPy ttest_ind
OSCVB-050,independent_t_welch,invalid_both_constant,invalid,Both variances zero,"{""group1"":[3,3,3],""group2"":[4,4,4],""alternative"":""two-sided""}",invalid_input,Welch formulas,SciPy ttest_ind
OSCVB-051,paired_t,typical,standard,Matched before/after,"{""before"":[10,12,9,14,11],""after"":[9,11,10,12,10],""alternative"":""two-sided""}",numeric_result,Difference-score formulas,SciPy ttest_rel
OSCVB-052,paired_t,greater,standard,Positive before-minus-after,"{""before"":[8,9,10,11,12],""after"":[7,8,9,10,10],""alternative"":""greater""}",numeric_result,Difference-score formulas,SciPy ttest_rel
OSCVB-053,paired_t,less,standard,Negative before-minus-after,"{""before"":[1,2,3,4,5],""after"":[2,3,4,5,7],""alternative"":""less""}",numeric_result,Difference-score formulas,SciPy ttest_rel
OSCVB-054,paired_t,small_n,boundary,Two pairs,"{""before"":[1,4],""after"":[2,2],""alternative"":""two-sided""}",numeric_result,Difference-score formulas,SciPy ttest_rel
OSCVB-055,paired_t,large_offset,stress,Large paired values,"{""before"":[1000002,1000004,1000005],""after"":[1000001,1000002,1000004],""alternative"":""two-sided""}",numeric_result,Difference-score formulas,SciPy ttest_rel
OSCVB-056,paired_t,tiny_diff,stress,Tiny differences,"{""before"":[1.000001,1.000003,1.000002,1.0],""after"":[1.0,1.000001,1.000003,0.999999],""alternative"":""two-sided""}",numeric_result,Difference-score formulas,SciPy ttest_rel
OSCVB-057,paired_t,mixed_sign,standard,Mixed signed values,"{""before"":[-2,-1,0,1,2],""after"":[-1,-2,1,0,3],""alternative"":""two-sided""}",numeric_result,Difference-score formulas,SciPy ttest_rel
OSCVB-058,paired_t,n_ten,standard,Larger paired sample,"{""before"":[10,11,13,12,14,15,12,16,13,17],""after"":[9,12,12,11,13,14,13,15,12,16],""alternative"":""two-sided""}",numeric_result,Difference-score formulas,SciPy ttest_rel
OSCVB-059,paired_t,invalid_lengths,invalid,Unequal vector lengths,"{""before"":[1,2,3],""after"":[1,2],""alternative"":""two-sided""}",invalid_input,Difference-score formulas,SciPy ttest_rel
OSCVB-060,paired_t,invalid_constant_diff,invalid,Constant differences,"{""before"":[2,3,4,5],""after"":[1,2,3,4],""alternative"":""two-sided""}",invalid_input,Difference-score formulas,SciPy ttest_rel
OSCVB-061,one_way_anova,three_groups,standard,Three ordinary groups,"{""groups"":[[1,2,3,4],[2,3,4,5],[5,6,7,8]]}",numeric_result,ANOVA sums-of-squares formulas,SciPy f_oneway
OSCVB-062,one_way_anova,four_groups,standard,Four groups,"{""groups"":[[10,11,9],[12,13,11],[10,10.5,11],[15,14,16]]}",numeric_result,ANOVA sums-of-squares formulas,SciPy f_oneway
OSCVB-063,one_way_anova,equal_means,standard,Similar means,"{""groups"":[[1,2,3],[2,2,2.5],[1.5,2,2.5]]}",numeric_result,ANOVA sums-of-squares formulas,SciPy f_oneway
OSCVB-064,one_way_anova,unbalanced,standard,Unequal group sizes,"{""groups"":[[1,2,3,4,5],[2,3,4],[6,7,8,9]]}",numeric_result,ANOVA sums-of-squares formulas,SciPy f_oneway
OSCVB-065,one_way_anova,large_offset,stress,Large location,"{""groups"":[[1000001,1000002,1000003],[1000002,1000003,1000004],[1000005,1000006,1000007]]}",numeric_result,ANOVA sums-of-squares formulas,SciPy f_oneway
OSCVB-066,one_way_anova,negative,standard,Negative values,"{""groups"":[[-5,-4,-3],[-3,-2,-1],[0,1,2]]}",numeric_result,ANOVA sums-of-squares formulas,SciPy f_oneway
OSCVB-067,one_way_anova,tiny_scale,stress,Tiny scale,"{""groups"":[[1e-08,2e-08,3e-08],[2e-08,3e-08,4e-08],[5e-08,6e-08,7e-08]]}",numeric_result,ANOVA sums-of-squares formulas,SciPy f_oneway
OSCVB-068,one_way_anova,many_values,standard,Thirty observations,"{""groups"":[[1,2,3,4,5,6,7,8,9,10],[3,4,5,6,7,8,9,10,11,12],[8,9,10,11,12,13,14,15,16,17]]}",numeric_result,ANOVA sums-of-squares formulas,SciPy f_oneway
OSCVB-069,one_way_anova,invalid_one_group,invalid,Only one group,"{""groups"":[[1,2,3]]}",invalid_input,ANOVA sums-of-squares formulas,SciPy f_oneway
OSCVB-070,one_way_anova,invalid_singleton,invalid,Group with one observation,"{""groups"":[[1,2,3],[4]]}",invalid_input,ANOVA sums-of-squares formulas,SciPy f_oneway
OSCVB-071,pearson_correlation,positive,standard,Strong positive association,"{""x"":[1,2,3,4,5,6],""y"":[2,4,5,8,10,11]}",numeric_result,Product-moment formula,SciPy pearsonr
OSCVB-072,pearson_correlation,negative,standard,Strong negative association,"{""x"":[1,2,3,4,5],""y"":[10,8,6,5,2]}",numeric_result,Product-moment formula,SciPy pearsonr
OSCVB-073,pearson_correlation,perfect_positive,standard,Perfect positive correlation,"{""x"":[1,2,3,4],""y"":[3,6,9,12]}",numeric_result,Product-moment formula,SciPy pearsonr
OSCVB-074,pearson_correlation,perfect_negative,standard,Perfect negative correlation,"{""x"":[1,2,3,4],""y"":[8,6,4,2]}",numeric_result,Product-moment formula,SciPy pearsonr
OSCVB-075,pearson_correlation,near_zero,boundary,Near-zero association,"{""x"":[1,2,3,4,5,6],""y"":[1,-1,1,-1,1,-1]}",numeric_result,Product-moment formula,SciPy pearsonr
OSCVB-076,pearson_correlation,large_offset,stress,Large location,"{""x"":[1000001,1000002,1000003,1000004],""y"":[2000005,2000007,2000008,2000010]}",numeric_result,Product-moment formula,SciPy pearsonr
OSCVB-077,pearson_correlation,tiny_scale,stress,Tiny scale,"{""x"":[1e-09,2e-09,3e-09,4e-09],""y"":[4e-09,1e-09,3e-09,2e-09]}",numeric_result,Product-moment formula,SciPy pearsonr
OSCVB-078,pearson_correlation,n_three,boundary,Smallest allowed n in benchmark,"{""x"":[1,2,4],""y"":[2,1,5]}",numeric_result,Product-moment formula,SciPy pearsonr
OSCVB-079,pearson_correlation,invalid_lengths,invalid,Unequal vector lengths,"{""x"":[1,2,3],""y"":[1,2]}",invalid_input,Product-moment formula,SciPy pearsonr
OSCVB-080,pearson_correlation,invalid_constant,invalid,Constant x,"{""x"":[1,1,1,1],""y"":[1,2,3,4]}",invalid_input,Product-moment formula,SciPy pearsonr
OSCVB-081,simple_linear_regression,positive,standard,Positive fitted line,"{""x"":[1,2,3,4,5],""y"":[2,4,5,8,10]}",numeric_result,Least-squares formulas,SciPy linregress
OSCVB-082,simple_linear_regression,negative,standard,Negative slope,"{""x"":[1,2,3,4,5],""y"":[10,8,7,4,2]}",numeric_result,Least-squares formulas,SciPy linregress
OSCVB-083,simple_linear_regression,perfect,standard,Perfect line,"{""x"":[1,2,3,4],""y"":[3,5,7,9]}",numeric_result,Least-squares formulas,SciPy linregress
OSCVB-084,simple_linear_regression,with_intercept,standard,Nonzero intercept,"{""x"":[0,1,2,3,4],""y"":[5,6.2,7.9,9.1,10.8]}",numeric_result,Least-squares formulas,SciPy linregress
OSCVB-085,simple_linear_regression,large_offset,stress,Large x location,"{""x"":[1000001,1000002,1000003,1000004],""y"":[2000003,2000005,2000007,2000009]}",numeric_result,Least-squares formulas,SciPy linregress
OSCVB-086,simple_linear_regression,tiny_scale,stress,Tiny scale,"{""x"":[1e-06,2e-06,3e-06,4e-06],""y"":[2e-06,2.5e-06,4e-06,5e-06]}",numeric_result,Least-squares formulas,SciPy linregress
OSCVB-087,simple_linear_regression,noisy,standard,Moderately noisy line,"{""x"":[1,2,3,4,5,6,7,8],""y"":[1,4,2,7,5,9,8,11]}",numeric_result,Least-squares formulas,SciPy linregress
OSCVB-088,simple_linear_regression,negative_x,standard,Negative and positive x,"{""x"":[-4,-3,-2,-1,0,1],""y"":[8,6,5,3,2,0]}",numeric_result,Least-squares formulas,SciPy linregress
OSCVB-089,simple_linear_regression,invalid_lengths,invalid,Unequal lengths,"{""x"":[1,2,3],""y"":[1,2]}",invalid_input,Least-squares formulas,SciPy linregress
OSCVB-090,simple_linear_regression,invalid_constant_x,invalid,Constant predictor,"{""x"":[2,2,2,2],""y"":[1,2,3,4]}",invalid_input,Least-squares formulas,SciPy linregress
OSCVB-091,chi_square_independence,two_by_two_no_correction,standard,2x2 Pearson chi-square,"{""table"":[[20,30],[10,40]],""correction"":false}",numeric_result,Expected-count formula,SciPy chi2_contingency
OSCVB-092,chi_square_independence,two_by_two_yates,standard,2x2 Yates correction,"{""table"":[[20,30],[10,40]],""correction"":true}",numeric_result,Expected-count formula,SciPy chi2_contingency
OSCVB-093,chi_square_independence,two_by_three,standard,2x3 table,"{""table"":[[10,20,30],[20,15,25]],""correction"":false}",numeric_result,Expected-count formula,SciPy chi2_contingency
OSCVB-094,chi_square_independence,three_by_three,standard,3x3 table,"{""table"":[[12,8,5],[7,15,8],[3,9,18]],""correction"":false}",numeric_result,Expected-count formula,SciPy chi2_contingency
OSCVB-095,chi_square_independence,balanced,standard,Exact independence,"{""table"":[[25,25],[25,25]],""correction"":false}",numeric_result,Expected-count formula,SciPy chi2_contingency
OSCVB-096,chi_square_independence,sparse,standard,Small expected cells,"{""table"":[[1,9],[8,2]],""correction"":false}",numeric_result,Expected-count formula,SciPy chi2_contingency
OSCVB-097,chi_square_independence,large_counts,stress,Large counts,"{""table"":[[10000,12000],[11000,9000]],""correction"":false}",numeric_result,Expected-count formula,SciPy chi2_contingency
OSCVB-098,chi_square_independence,unbalanced_margins,standard,Highly unequal margins,"{""table"":[[50,1,2],[3,20,4]],""correction"":false}",numeric_result,Expected-count formula,SciPy chi2_contingency
OSCVB-099,chi_square_independence,invalid_negative,invalid,Negative count,"{""table"":[[1,-1],[2,3]],""correction"":false}",invalid_input,Expected-count formula,SciPy chi2_contingency
OSCVB-100,chi_square_independence,invalid_zero_row,invalid,Zero row total,"{""table"":[[0,0],[2,3]],""correction"":false}",invalid_input,Expected-count formula,SciPy chi2_contingency
OSCVB-101,fisher_exact_2x2,two_sided,standard,Classic small-table example,"{""table"":[[1,9],[11,3]],""alternative"":""two-sided""}",numeric_result,Hypergeometric enumeration,SciPy fisher_exact
OSCVB-102,fisher_exact_2x2,greater,standard,One-sided greater,"{""table"":[[8,2],[1,5]],""alternative"":""greater""}",numeric_result,Hypergeometric enumeration,SciPy fisher_exact
OSCVB-103,fisher_exact_2x2,less,standard,One-sided less,"{""table"":[[1,5],[8,2]],""alternative"":""less""}",numeric_result,Hypergeometric enumeration,SciPy fisher_exact
OSCVB-104,fisher_exact_2x2,zero_cell,boundary,Zero cell,"{""table"":[[0,5],[4,1]],""alternative"":""two-sided""}",numeric_result,Hypergeometric enumeration,SciPy fisher_exact
OSCVB-105,fisher_exact_2x2,balanced,standard,Balanced table,"{""table"":[[5,5],[5,5]],""alternative"":""two-sided""}",numeric_result,Hypergeometric enumeration,SciPy fisher_exact
OSCVB-106,fisher_exact_2x2,large_counts,stress,Larger exact table,"{""table"":[[100,120],[90,130]],""alternative"":""two-sided""}",numeric_result,Hypergeometric enumeration,SciPy fisher_exact
OSCVB-107,fisher_exact_2x2,separation,standard,Complete separation,"{""table"":[[10,0],[0,10]],""alternative"":""two-sided""}",numeric_result,Hypergeometric enumeration,SciPy fisher_exact
OSCVB-108,fisher_exact_2x2,small_counts,standard,Very small counts,"{""table"":[[1,1],[1,2]],""alternative"":""two-sided""}",numeric_result,Hypergeometric enumeration,SciPy fisher_exact
OSCVB-109,fisher_exact_2x2,invalid_shape,invalid,Not 2x2,"{""table"":[[1,2,3],[4,5,6]],""alternative"":""two-sided""}",invalid_input,Hypergeometric enumeration,SciPy fisher_exact
OSCVB-110,fisher_exact_2x2,invalid_negative,invalid,Negative count,"{""table"":[[1,-1],[2,3]],""alternative"":""two-sided""}",invalid_input,Hypergeometric enumeration,SciPy fisher_exact
OSCVB-111,confidence_interval_mean,t_95,standard,95% t interval,"{""method"":""t"",""data"":[12,15,14,10,13,16],""confidence"":0.95}",numeric_result,Critical-value formula,Statsmodels/SciPy interval
OSCVB-112,confidence_interval_mean,t_90,standard,90% t interval,"{""method"":""t"",""data"":[5.1,5.3,5.2,5.4,5.0],""confidence"":0.9}",numeric_result,Critical-value formula,Statsmodels/SciPy interval
OSCVB-113,confidence_interval_mean,t_small_n,boundary,n=2 t interval,"{""method"":""t"",""data"":[1,4],""confidence"":0.95}",numeric_result,Critical-value formula,Statsmodels/SciPy interval
OSCVB-114,confidence_interval_mean,t_large_offset,stress,Large location,"{""method"":""t"",""data"":[1000001,1000002,1000003,1000004],""confidence"":0.99}",numeric_result,Critical-value formula,Statsmodels/SciPy interval
OSCVB-115,confidence_interval_mean,t_tiny_scale,stress,Tiny scale,"{""method"":""t"",""data"":[1e-08,2e-08,3e-08,4e-08],""confidence"":0.95}",numeric_result,Critical-value formula,Statsmodels/SciPy interval
OSCVB-116,confidence_interval_mean,z_95,standard,Known sigma 95%,"{""method"":""z"",""mean"":50,""sigma"":10,""n"":100,""confidence"":0.95}",numeric_result,Critical-value formula,Statsmodels/SciPy interval
OSCVB-117,confidence_interval_mean,z_99,standard,Known sigma 99%,"{""method"":""z"",""mean"":3.5,""sigma"":0.8,""n"":64,""confidence"":0.99}",numeric_result,Critical-value formula,Statsmodels/SciPy interval
OSCVB-118,confidence_interval_mean,z_large_n,stress,Very large n,"{""method"":""z"",""mean"":1000,""sigma"":250,""n"":1000000,""confidence"":0.95}",numeric_result,Critical-value formula,Statsmodels/SciPy interval
OSCVB-119,confidence_interval_mean,invalid_confidence,invalid,Invalid confidence,"{""method"":""z"",""mean"":10,""sigma"":2,""n"":20,""confidence"":1.2}",invalid_input,Critical-value formula,Statsmodels/SciPy interval
OSCVB-120,confidence_interval_mean,invalid_n,invalid,n<2 for t interval,"{""method"":""t"",""data"":[5],""confidence"":0.95}",invalid_input,Critical-value formula,Statsmodels/SciPy interval