Research Guide
Master the art of nutritional data processing and academic reporting — for both 24-hour dietary recalls and Food Frequency Questionnaires (FFQ).
Built for Chapter 4
Chapter 4 of your thesis is the most data-intensive. FoodQuant is specifically engineered to generate the complex nutritional tables, respondent demographics, and FFQ statistical summaries required by most academic boards.
Academic Standard
Our tables follow APA and Vancouver reporting styles for nutritional intake studies.
Thesis Ready
Methodology Design
Learn how to structure your research data — whether 24-hour dietary recalls or Food Frequency Questionnaires (FFQ) — for seamless integration with our processing engine.
Step 1: Collection
Guidelines for collecting accurate respondent recall data.
Step 2: Cleaning
How to handle raw data cleaning before uploading to the platform.
Step 3: Exporting
Finalizing your analysis and exporting statistical summaries.
Step 1: Upload FFQ
Import your FFQ spreadsheet — the system auto-detects variables, response types, and numeric values.
Step 2: Analyze
Generate descriptive statistics, cross-tabulations, and AI-powered dietary insights automatically.
Step 3: Report
Export cross-tabulation reports and AI summary reports formatted for your thesis.
Peer-Reviewed Databases
Data Integrity
We ensure the highest level of scientific accuracy by cross-referencing all food items against validated nutritional databases used by top academic institutions.
Exporting for Journals
Statistical Summary
Get mean, standard deviation, and percentage distribution of nutrients for your population.
RDA Gap Analysis
Visual charts and tables showing intake vs. recommended dietary allowances.
FFQ Cross-Tabulation
Export custom cross-tabulation tables and AI-generated reports for FFQ-based studies.
Join the Research Community
Connect with other researchers using FoodQuant to share methodology tips and analysis best practices.
Start Your Research