The Stat Kiste is a collection of statistical methods from various sources that I used throughout the last few years. Each method can be called from the command line.

Currently, the Stat Kiste contains the following implementations:

• AUC with Confidence Intervals: Fast DeLong method for binary classification, implementation by the Yandex Data School https://github.com/yandexdataschool/roc_comparison
• Extended Classification Report: Report for multiclass classification that calculates the accuracy, precision, recall, f1-score, support, predicted values, AUC (sklearn), AUC (DeLong), AUC COV, and AUC Confidence Intervals based on a given alpha value for one-vs-all. Additionally, the report lists the average/total for precision, recall, f-1 and accuracy as well as the overall AUC (sklearn) and the sum of support and predicted values.
• Normality Tests: Shapiro-Wilk test, Anderson-Darling Test, and D'Agostino-Pearson
• Mean Tests: Wilcoxon Signed Rank Test and Paired T-test

Calculating the AUC with Confidence Intervals based on a given alpha and a csv-file that contains y_score and corresponding y_true values from a binary classification problem. Prints a confusion matrix.

python run.py --function ci_auc -f <path_to_csv_file> -ysc <y_score_column> -ytc <y_true_column> -a <alpha>

Example source code is provided in examples/example_ci_auc.py.

An example csv file is provided in examples/data_ci_auc.csv.

Run the extended Classification Report based on a csv-file that contains y_pred, y_score, and corresponding y_true values from a binary or multiclass classification problem. Prints a confusion matrix.

python run.py --function classification_report -f <path_to_csv_file> -ysc <y_score_column> -ytc <y_true_column> -ypc <y_pred_column> -a <alpha>

Example source code is provided in examples/example_classification_report.py.

An example csv file is provided in examples/data_classification_report.csv.

Run a normality test on data stored in a csv file.

python run.py --function normality -test <anderson/shapiro/dagostino> -f <path_to_csv_file> -vc <value_column> -a <alpha>

Example source code is provided in examples/example_normality_tests.py.

An example csv file is provided in examples/data_normality.csv.

Run a mean test on data stored in a csv file.

python run.py --function mean -test <wilcoxon/pairedt> -f <path_to_csv_file> -s1c <sample1_column> -s2c <sample1_column> -a <alpha>

Example source code is provided in examples/example_mean_tests.py.

An example csv file is provided in examples/data_mean.csv.