Service
Biostatistics & Data Analysis
Sample size, descriptive and inferential statistics, regression, survival and diagnostic test analysis in SPSS, R, STATA or Python — with interpretation you can explain.
The challenge
Why this matters
Statistics is where many good studies stumble: the wrong test for the data type, unchecked assumptions, or results that are reported but not understood. Reviewers and examiners notice. Professional analysis — explained clearly — lets you present your findings with confidence.
What we help with
- Sample size and power calculation
- Data cleaning, coding and variable preparation
- Descriptive statistics and baseline tables
- Inferential statistics — t-tests, ANOVA, chi-square, non-parametric tests
- Correlation and regression — linear, logistic, Poisson, Cox
- Survival analysis — Kaplan–Meier curves and log-rank tests
- Diagnostic test analysis — sensitivity, specificity, ROC/AUC
- Agreement and reliability — kappa, ICC, Bland–Altman
- Publication-quality tables and figures
- Interpretation of statistical results in plain language
Deliverables
What you receive
Exact deliverables are confirmed in your written scope before work starts.
Statistical analysis plan (SAP) for your objectives
Clean, documented analysis output (SPSS / R / STATA / Python)
Formatted results tables and figures
Interpretation notes for each analysis
Explanation session so you can defend the analysis
Process
How we work together
- 01
Submit your requirement
Tell us about your study, topic, institution and current stage. Upload documents if you have them.
- 02
Free research consultation
A research coordinator reviews your requirement and discusses it with you.
- 03
Scope & research plan
We define the exact deliverables, timeline and responsibilities — in writing, before any work begins.
- 04
Expert support
Work progresses through structured milestones, with your review at each stage.
- 05
Final review
Deliverables are reviewed, explained and finalised with you.
Example outputs
The kind of work you can expect
Illustrative formats only — every output is prepared from your own study and data.
Baseline characteristics table
Kaplan–Meier curve
ROC curve with AUC
Regression table with odds ratios and 95% CI
FAQs
Questions about biostatistics
Which software do you use?
SPSS, R, STATA and Python. If your institution or journal prefers a particular package, we use that one and can share the syntax or code.
Will you change my data to get significant results?
Never. We analyse the data you collect exactly as it is. Non-significant results are valid results, and we help you report and interpret them properly.
Can you calculate sample size before I start?
Yes. We need your primary outcome, expected effect size or prevalence from the literature, and your study design. We explain every assumption used.
Do you provide statistical analysis?
Yes. We provide sample size calculation, descriptive and inferential statistics, regression, survival and diagnostic test analysis in SPSS, R, STATA or Python, along with plain-language interpretation of every result.
Do you help with sample size calculation?
Yes. We calculate sample size based on your primary outcome, design and values from published literature, and document every assumption so you can justify it to your department or ethics committee.
Can you help with SPSS?
Yes. We can run analyses in SPSS, share the syntax, and also teach you how to reproduce and understand the output.
Not sure what you need?
Talk to a Research Consultant
Share your requirement and a consultant will review it with you. You’ll receive a clear scope and quote before anything begins.