Biostatistics & Data Analytics

Sound statistics turn data into decisions.

Why It Matters

From sample size and analysis plans to PRISMA-compliant systematic reviews and meta-analyses, we deliver analysis that is accurate, transparent and ready for review or publication.

Who It Is for

Investigators, Ph.D. scholars, faculty, hospitals, sponsors and CROs.

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What We Cover

Sample size calculation and statistical analysis plans
Descriptive and inferential statistics and modelling
Systematic reviews and meta-analyses following PRISMA (pairwise and network)
Analysis in SPSS, GraphPad Prism, R, Python and Base SAS

Benefits

Defensible Design

Sample size and power justified in writing.

Right Methods

Tests chosen for your data and question.

Clear Outputs

Publication-ready tables and figures.

Transparent

Analysis code and logs you can share with reviewers.

Related Courses

Data, statistics & AI

Biostatistics for Clinical & Health Research

Study design, sample size and analysis you can defend, using SPSS, GraphPad Prism and R.

6 weekends
Live online with recordings · Next batch: on request
Postgraduates, PhD scholars, faculty and data aspirants

What you will learn

Study designs and hypothesis testing
Sample size and power
Choosing the right test
Regression and survival analysis basics
Systematic reviews and meta-analysis (PRISMA)

Data, statistics & AI

Clinical Data Analytics: Excel, SQL, R & Python

Clean, query, summarise and visualise clinical study data with the tools teams use daily.

6 weekends
Live online with recordings · Next batch: on request
Graduates moving into data roles

What you will learn

Excel for clinical data
SQL for querying study data
R and Python basics for analysis
Tables, listings and figures
Dashboards for trial metrics

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