Technologies / Data & Analytics

Data Architecture, Statistical Foundations and Calculation Automation - GraphPad Prism

A two-day GraphPad Prism training covering data architecture, Data Wrangling, statistical inference, nonlinear regression, Kaplan-Meier survival analysis, Principal Component Analysis (PCA), and workflow automation with publication-ready export. The program combines theory with practical case studies, including qPCR analysis automation.

Data Architecture, Statistical Foundations and Calculation Automation - GraphPad Prism is a two-day, intensive EITT training program, delivered on-site or remotely — depending on participant preferences. The program is designed for individuals with basic experience — classes combine theory with intensive practical exercises.

Topics covered include:

Work Environment and Data Wrangling
Statistical Inference – Algorithmic Approach
Case Study – qPCR Analysis Automation
Nonlinear Regression and Curve Fitting
Survival Analysis
Principal Component Analysis (PCA) – Big Data in Biology
Workflow Automation and Export (Deployment)

Participants will leave the training with practical knowledge and tools for immediate application in their daily work.

Benefits

The participant will learn GraphPad Prism file architecture and how to effectively manage data across 8 table types
Will master data wrangling techniques — inspection, logarithmic transformations, and normalization
Will gain the ability to perform normality tests, clean data using the ROUT algorithm, and apply statistical tests (t-test, ANOVA)
Will learn to automate qPCR analysis using the Delta-Delta Ct method with proper replicate handling
Will master nonlinear regression — fitting dose-response curves, determining IC50, and interpolation
Will learn Kaplan-Meier survival analysis with Log-rank tests and Hazard Ratio interpretation
Will understand the principles of Principal Component Analysis (PCA) and its application to multidimensional data
Will learn to automate workflows (Magic, The Wand, cloning) and export graphs according to publication standards

Who is this training for?

Data analysts and statisticians working with biomedical and laboratory data

Scientists and researchers in biology, medicine, and life sciences

Quality control and validation specialists in pharmaceutical and biotechnology companies

PhD students and academic staff using statistical analysis in research

Laboratory engineers and technicians responsible for experimental results analysis

Research project managers needing to understand data analysis methods

Prerequisites

Basic knowledge of descriptive statistics (mean, standard deviation, normal distribution)
Proficiency in working with spreadsheets (Excel or similar)
Basic familiarity with the GraphPad Prism environment or willingness to quickly learn the interface
Knowledge of laboratory or biomedical data context will be an additional advantage

Training program

File architecture — differences between .prism format (new standard) and .pzfx (compatibility)
Why a project file is more than a spreadsheet
Table taxonomy (Data Mapping) — overview of 8 table types in Prism
Data inspection — using the Inspect tool for rapid data quality verification
Transformations — using built-in functions for data logarithm and normalization

Data distribution — automatic normality testing (Shapiro-Wilk, D'Agostino-Pearson)
Data cleaning (Outliers) — ROUT algorithm (Robust regression and Outlier removal)
Group comparisons (A/B Tests) — Student's t-test (comparing 2 variables)
ANOVA (Analysis of Variance) — logic of comparing multiple groups
Multiple Comparisons Problem — choosing the appropriate correction (Tukey, Bonferroni) to prevent False Positive errors

Delta-Delta Ct method mathematics — how Prism handles relative gene expression quantification
Replicate handling — distinguishing technical replicates (averaging) from biological replicates (data points)
Visualization — creating bar charts with individual data points (Scatter plot with Bar)

Regression logic — difference between correlation and model fitting (Fit)
Dose-Response curves — determining the IC50 parameter (inhibitory concentration)
Constraints — restricting model parameters
Interpolation — calculating X values for a given Y based on a standard curve (e.g., ELISA assays)

Survival data structure — coding events and censored data
Kaplan-Meier curves — generating step-function plots
Comparative tests — Log-rank test (Mantel-Cox) — algorithm for comparing two curves
Risk — interpreting the Hazard Ratio (HR) table

PCA operating principle — how to flatten multidimensional data into 2D/3D plots without losing information
Standardization — why (and how) to scale data before analysis (Centering/Scaling)
Interpretation — Score Plot and Loadings Plot

Magic (Make Graphs Consistent) — tool for batch formatting graphs with one click
The Wand (Analysis Wizard) — copying the entire analytical pipeline to new data
Cloning — creating experiment templates (Templates)
Prism Cloud — introduction to cloud collaboration
Export and publication standards — vector formats (PDF, EPS, EMF) vs raster (TIFF)
Understanding DPI and compression
Preparing Composite Figures (multi-graph layouts) directly in Prism (Layouts)

Delivery Methods

Online

Convenience of participating from anywhere
Interactive live sessions with trainer
Materials available for 30 days
No travel costs

On-site

Direct contact with trainer and group
Intensive hands-on workshops
Networking with other participants
Full focus on learning

Training Topics

Frequently asked questions

What is the format and duration of the 'Data Architecture, Statistical Foundations and Calculation Automation - GraphPad Prism' training?

The training lasts 2 days and is delivered both on-site and remotely (online) — depending on the group's preferences. The program includes lectures, demonstrations, and practical exercises, ensuring a comprehensive approach to the subject matter.

What are the prerequisites for participants?

The training is at the intermediate level — it assumes basic experience with the topic. We expect participants to have: Basic knowledge of descriptive statistics (mean, standard deviation, normal distribution), proficiency in working with spreadsheets (excel or similar), basic familiarity with the graphpad prism environment or willingness to quickly learn the interface, knowledge of laboratory or biomedical data context will be an additional advantage. Detailed requirements can be found in the 'Prerequisites' section on this page.

Does the training include practical elements?

Yes, the program combines theory with practice. Participants work on case studies, take part in group exercises and practical workshops. Each exercise concludes with a debrief and feedback from the instructor.

Will I receive a certificate after the training?

Yes, each participant receives a personalized certificate of completion issued by EITT, confirming participation in the program and the competencies acquired.

What is the cost of the training and how can I register?

The training costs PLN 1 770 net per person. To register for the training or to receive a group offer, contact us by phone or through the form on our website. We also offer closed training sessions tailored to the needs of a specific organization.