About this tool

ESCAP (Easy Statistics, Chemometrics and Plotting) is a user‑friendly application designed to escape the complexity of data analysis. It brings together essential tools, descriptive statistics, advanced plots & maps, PCA, PLSR, Correlation and related methods into a single, intuitive interface. Whether you are exploring experimental data, teaching chemometrics, or conducting routine analysis, ESCAP helps you move quickly from raw data to clear, reproducible insights with zero coding. ESCAP is accessible at analysis.gau.edu.bd


Example files

Download an example CSV dataset and an example PDF with instructions:

Download example CSV Download example PDF

Sample data


Instructions for Users

  1. Please see the attached PDF.
  2. Always upload data in CSV format.
  3. Remember to click 'Clear all inputs' when switching between univariate and multivariate analysis.
  4. Figures are generated in high quality; if you need to edit them, use the PDF or SVG downloads.
  5. If you find any problem, please email me.

Author

Dr. Md. Nahidul Islam
Dr. Md. Nahidul Islam
Assistant Professor
Department of Food Engineering
Faculty of Agricultural and Bioresources Engineering
Gazipur Agricultural University (GAU), Gazipur-1706, Bangladesh
nahidul.islam@gau.edu.bd

Download citation (EndNote format)
Download citation.enw

Uploaded data (latest file; first 20 rows; first 15 columns)



Publication Ready ANOVA Table




ANOVA Summary Table


Publication Ready Chi Square Table

If your dataset contains more than one species, please select that column in "Select condition (ANOVA) optional /Species / *ID column (circular plot)".


Preprocessed X‑matrix

Preprocessed Data: Uploaded in the Multivariate field (with chosen variables).


PCA – Eigenvalues and Explained Variance



PCA – Loadings (first few PCs)


PCA – Scores


X/Y block variance


PLSR – Model performance


Regression coefficients, VIP, Selectivity Ratio


Q residuals and Hotelling T²


Correlation matrix: (Spearman's rank-order correlation)



Correlation matrix: (Pearson product–moment correlation)




Please select ID, Treatment, and Responses from the left Panel
Download Sample Data
Violin/box plot with statistical comparisons
Download Sample Data
Select Treatment and Response Variables from the left Panel
and choose the plot number to download
Download Sample Data
Select Two Factors and Response Variables from the left Panel (Factor which have lower leves, should select first)
and choose the plot number to download
Download Sample Data
Use the selector from the left panel to toggle between HEATMAPS

Row and column clustering use Euclidean distance with hierarchical (complete-linkage) clustering.

Download Sample Data
Use the selector from the left panel to toggle between Dendograms

Dendrograms are computed from Euclidean distances on PCA scores using hierarchical clustering (Ward.D2 linkage).







                      
                      
                    




                      
                      
                    




Download graph as PNG Download graph as PDF Download graph as SVG

Study areas


Download PNG Download PDF Download SVG

Disclaimer

ESCAP is provided on an “as is” basis, without any warranties of any kind. To the fullest extent permitted by applicable law, the author makes no representations or warranties, express or implied, including (but not limited to) implied warranties of merchantability, fitness for a particular purpose, accuracy, completeness, or non‑infringement.

ESCAP is designed for exploratory, educational, and research purposes. It is not intended to replace professional statistical, scientific, medical, legal, regulatory, or other expert advice. The methods, results, and interpretations produced by this software may not be appropriate for every dataset, application, or regulatory context.

By using this app, you acknowledge and agree that you are solely responsible for:

  • Selecting suitable data, models, options, and settings;
  • Checking and validating all outputs, summaries, and figures;
  • Determining whether the analyses and assumptions are appropriate for your specific use case; and
  • Any conclusions, decisions, reports, or actions that rely on results generated by this app.

Under no circumstances shall the author be liable for any kind of loss or damage arising from or related to the use of, or inability to use, ESCAP. This includes, without limitation, direct, indirect, incidental, consequential, special, punitive, or exemplary damages, as well as loss of data, loss of income or profit, business interruption, or claims by third parties, even if the possibility of such damages has been advised.

By accessing or using this app, you indicate that you have read, understood, and agree to be bound by this disclaimer.