Analysis completed with statistical methodology and expert verification.
Measurement model · maximum likelihood
| Fit index | Value | Criterion | Result |
|---|---|---|---|
| χ² / df | 1.62 | < 3.00 | Met |
| CFI | .981 | ≥ .95 | Met |
| TLI | .975 | ≥ .95 | Met |
| RMSEA | .034 | ≤ .06 | Met |
| SRMR | .029 | ≤ .08 | Met |
Standardised loadings .77 to .88 all p < .001 · AVE .61 to .74 · CR .83 to .91
Two arms · reverse Kaplan Meier follow up
| Group | n | Events | Median | 95% CI |
|---|---|---|---|---|
| Intervention | 110 | 68 | 27.4 | [22.1, 33.8] |
| Standard care | 110 | 88 | 18.6 | [15.4, 22.0] |
| Hazard ratio | 0.68 | [0.49, 0.94] |
Log rank χ²(1) = 5.71 p = .017 · median follow up 34.2 months
Every figure below comes from work already delivered. Analyses are checked against the same reference outputs as R and Python, reported in the format journals expect, and reviewed by a methodologist before release
Students, university departments and analytics teams run their studies here rather than maintaining their own statistical stack
Assumption checks, post hoc tests and reporting tables that take a week by hand are returned the same day
Every methodology is verified to return the same estimates as the core statistical libraries, with APA formatted output
From paired t-tests to structural equation models and survival analysis, delivered with the diagnostics that justify the choice
Four things take most of the time in an analysis, and none of them is the thinking you were trained to do. Here is what each one costs you and what replaces it
You know the question but not which test survives review. A methodologist reads your data structure and names the method, the robustness check and the reason
A week disappears into syntax errors and package versions. You upload a file and the analysis runs against the same engines as R and Python
An agency quotes four figures and three weeks for one model. A subscription costs less than an hour of that and returns results the same day
Rebuilding tables to match a journal template is unpaid labour. Output arrives in APA format with the assumption checks a reviewer will ask for
Explore a wide range of analytical frameworks ready for immediate use in practice and research
Prove the questionnaire measures what it claims, then model the paths beneath it
Compare groups and conditions with the assumption checks a reviewer will ask for
Separate trend from season and put an honest interval around what comes next
Show the intervention caused the change rather than the trend that was already there
Find the groups hiding in your data and describe what makes each one distinct
Model time to an event when some cases have not reached it yet
Predict an outcome and show which variables carried the prediction
Turn open ended answers into themes you can report and defend
Test whether location or connection explains the pattern you are seeing
Measure what people actually trade off when they choose between options
Different goals require different deliverables. We’ve built three distinct formats to match your specific needs
| Block | ΔR² | F change | β | 95% CI |
|---|---|---|---|---|
| 1 Controls | .06 | 3.41 | — | — |
| 2 Job characteristics | .15 | 12.80 | 0.34 | [.21, .47] |
| 3 Autonomy × support | .07 | 8.62 | 0.22 | [.09, .35] |
| Indirect effect | — | — | 0.18 | [.09, .29] |
| Total R² = .28 · F(9,402) = 17.4 · N = 412 | ||||
| Model | sMAPE | MASE | RMSSE | Coverage |
|---|---|---|---|---|
| Seasonal naive | 9.42 | 1.00 | 1.00 | — |
| Holt Winters | 6.18 | 0.71 | 0.74 | 0.88 |
| Gradient boosting | 5.03 | 0.58 | 0.61 | 0.90 |
| Temporal fusion transformer | 4.11 | 0.47 | 0.49 | 0.94 |
| Diebold Mariano vs gradient boosting, p = .004 | ||||
No dedicated data team required. A single dataset upload delivers raw CSV, visualization graphics, and executive PDF reports—ready to share company wide instantly
Four steps from a spreadsheet to a result you can submit, with a methodologist checking the choice before anything runs
“Being able to drop visualisations and quantitative indicators straight into a market research presentation lifted our client satisfaction noticeably. We used to spend days on data cleaning and statistical processing and had almost no time left to sharpen the insight. That order is now completely reversed.”
“Learning a statistics package and then picking up coding on top of it nearly cost me a full semester of my master’s thesis. Now I just tidy the data, upload it, and results come back within days, formatted in APA style so I can paste them straight into the manuscript. It carried me through to journal submission without a delay.”
“My field is organisational psychology, so structural equation modelling and moderated mediation were unavoidable. I kept misspecifying the bootstrap settings and the estimates never settled. Here the methodology comes with standard settings and the fit indices arrive laid out in a table, which cut my review time dramatically.”
Discounts and credits for students, supervisors, societies and research institutes. Verify once and the code arrives by email.
This exclusive discount is designed for undergraduate and graduate students carrying the financial burden of coursework and thesis writing. Undergraduate students who have completed at least four semesters, as well as graduate students who are currently enrolled (including completion and research status) or on leave, are eligible. A Pro plan discount code will be sent to your verified university email.
Pro and Smart subscribers receive a 50% discount coupon for the Quorant Certified Analytics Professional (QCAP) exam. Annual subscribers receive one free exam voucher. Upon earning the certification, you will receive a verified certificate ready to be added to your resume.
Invite fellow researchers or teammates to Quorant. When your referee completes their first subscription, both you and your peer will immediately receive one free voucher for an expert analytics report.
Exclusive partnership benefits for participants of Quorant affiliated academic conferences and researchers at private research institutes. Enter your institutional affiliate code to unlock an extra 20–30% discount across all plans, along with customized corporate and institutional licensing options.
We are looking for graduate students to shape the academic research ecosystem together with Quorant. Selected ambassadors receive unlimited access to all Smart features during their term, coauthor research papers with the Quorant team, and participate in various projects.
Bridging the global research divide for students, graduate students, and researchers in UN-designated target regions or under resourced research environments. Granted after a brief review of your research proposal, providing a 50% discount on the Smart plan along with one year of dedicated technical research support.
Send your university email or institutional affiliation and we will tell you which benefits you qualify for, usually within one business day.
A process built to turn a raw spreadsheet into evidence that holds up in review, with a methodologist accountable at every step
Drop a spreadsheet and the file is parsed on arrival
Excel, CSV and PDF are read directly. Column types, missing values and the shape of the data are detected before you answer a single question, so the first thing you see is what we understood rather than a form to fill in.
Assumptions are tested before a method is chosen
Normality, variance, independence and multicollinearity are checked on your data, not assumed. Where an assumption fails, the diagnosis names the consequence and the alternative that survives it.
A methodologist names the method and the reason
One of twenty four specialists is assigned by the shape of your problem. You receive the primary method, a robustness check, what goes wrong with the obvious alternative, and what a reviewer would otherwise attack.
The analysis runs against the same engines you would use
Estimates are produced with the libraries your field already trusts and verified against reference outputs. Long running models report progress rather than leaving you with a spinner.
A human reads the output before it reaches you
The specialist checks that the assumptions held, that the effect size is reported beside the p value, and that nothing in the table contradicts the diagnostics. On Smart this includes a written defence note.
Everything arrives in the format you will actually use
Tables formatted to APA 7, figures at presentation resolution, the raw output and the script that produced it. Nothing needs retyping and the analysis can be rerun by anyone who asks.
Upload a dataset and the first diagnosis arrives the same day
The statistics do not change between a thesis and a pricing decision, but the question, the deliverable and the person who has to defend it do
Papers, theses and grant reports
Show the questionnaire measures the construct before you argue anything with it
Confirmatory factor analysis, measurement invariance, reliabilityTest whether the programme moved the outcome, not just the season
Mixed design ANOVA, multilevel growth, propensity matchingModel when something happens when many cases have not reached it yet
Kaplan Meier, Cox regression, competing risksPool findings across studies and show whether they actually agree
Meta analysis, heterogeneity, publication biasPricing, demand and product decisions
Find the price where margin and volume stop fighting each other
Discrete choice, hierarchical Bayes, Van WestendorpPlan inventory and headcount against a number with an interval on it
State space models, temporal fusion transformer, hierarchical reconciliationSplit the base into groups that behave differently, not groups that look different
Latent class analysis, Gaussian mixture, RFM modellingLearn which claim moves intent before the campaign budget is committed
MaxDiff, conjoint, uplift modellingEvaluation, equity and regional analysis
Attribute the change to the intervention in a way an auditor accepts
Difference in differences, synthetic control, regression discontinuityShow where an effect concentrates rather than reporting a national average
Spatial autocorrelation, geographically weighted regression, small area estimationMake a sample speak for the population it was drawn from
Raking, post stratification, design effectsPut a defensible number on what a unit of outcome costs to buy
Incremental cost effectiveness, bootstrap intervals, sensitivity analysisRetention, risk and operations
Know which accounts are leaving and which lever still reaches them
Gradient boosting, survival analysis, uplift modellingRank exposure with a model you can explain to a regulator
Regularised logistic regression, SHAP attribution, calibrationSeparate a real shift from ordinary variation on the line
Statistical process control, design of experiments, capability analysisTurn thousands of open comments into themes with evidence behind them
Structural topic models, embeddings, sentiment classificationA 24 item scale was returning a fit index below the threshold reviewers accept. The specialist identified two cross loading items, recommended a bifactor specification and supplied the invariance tests the journal asked for on revision.
CFI moved from .885 to .961Pricing was set by competitor benchmarking. A choice experiment across 1,240 respondents estimated part worth utilities by segment and simulated share at six price points before the range was locked.
Margin held at a 9% higher list priceA subsidy had launched in one district and not another. Parallel trends failed on inspection, so a synthetic control was built from 24 donor districts and the effect was reported with a placebo distribution.
Effect survived every placebo testDescribe the question in your own words and a specialist will name the method
Explore an expansive library of frameworks built for complex research questions, then plug the one that matches your project straight into an analysis request
Click a research goal and we will lay out the methodology pipeline built for it.
The Quorant analytics team will recommend the optimal framework for you.
Get the exact analysis solution you need, right when you need it.
Start with the foundations: hypothesis testing, correlation, regression and clustering, run on your own.
For theses and professional reports. Structural equation modelling, multilevel, panel, time series and survival analysis.
The full library with human verification. Deep learning, causal inference and a methodologist who signs off on your results.
Have a code from a campus event, a partner programme or a conference booth? Enter it here and the discount is applied at checkout.
Dedicated specialists and volume terms built around how your team actually works
Quorant is a global research data infrastructure platform that transforms the process from the moment a researcher formulates a core hypothesis to the arrival at academically and practically definitive answers, delivered with unmatched precision and speed.
Even in today's advanced environment, countless researchers and enterprise R&D organizations remain trapped in severe inefficiencies. Excessive learning costs spent mastering complex analytical tools, heavy consulting processes that take months to initiate, and fragmented software delay the pace of research. The means, data analysis, is encroaching upon the true purpose: research itself.
Quorant was founded to eliminate these friction points from the market entirely. We introduce a paradigm shift where leading insights are derived instantly from your data and questions alone.
Quorant's core competitive edge lies in our Hybrid Processing Engine, which unifies the transformative speed of next generation AI computing with the uncompromising rigor of domain experts.
The moment data is uploaded, essential output metrics and explainable AI (XAI) based interpretations are generated flawlessly. Researchers can swap dozens of models in real time without time or cost constraints, pushing the boundaries of their hypotheses.
True failure in data analysis stems not from simple computational errors, but from models where statistical assumptions clash with the core research question. Quorant integrates a secondary verification process where domain experts rigorously review model validity and assumptions, ensuring fully reproducible integrity.
The generation of knowledge and the pace of innovation should never be constrained by technical learning curves or budget limits.
Our mission is singular: to reduce the distance to data analysis to Zero, creating an environment where researchers worldwide can focus exclusively on fundamental questions and breakthrough ideas. Alongside a continuously evolving analytical ecosystem, Quorant is setting the new global standard for research data.
Where your greatest questions are proven
by overwhelming data at unmatched speed.
Quorant
Effective Date: July 31, 2026
Quorant (“Quorant”, “we”, “us” and “our”) treats the private nature of your personal information seriously. This policy (the “Policy”) describes how we collect, use, store, disclose and delete information when you visit www.quorant.io (the “Site”) or register to use our data analytics platform and related services (the “Services”).
Quorant is operated from the City of Toronto, Ontario, Canada, and serves researchers and organisations in many countries. This Policy describes what we actually do. Where a practice is still developing, we say so rather than describing an intention as though it were already in place.
Please read this Policy carefully. If you do not agree with it, your only option is not to access the Site or the Services and not to provide us with personal information.
When you run an analysis you upload a dataset. That file, the methodology you select, the parameters you set and the outputs generated from it are together referred to in this Policy as Research Data. Research Data is processed on your instructions and for the sole purpose of producing the analysis you requested.
Research Data may contain personal information about third parties, for example survey respondents or study participants. Where that is the case, you are the controller of that information and Quorant acts on your behalf. Section 4.3 sets out what we ask of you before you upload.
When you use the Services, our hosting and storage providers record standard operational information such as server requests, timestamps, IP address, browser type and error logs. We use this to operate the platform and diagnose faults. It is not combined with your datasets and is not used to build a profile of you.
Quorant does not set cookies. To keep the Site working across page loads we store a small number of values in your browser's local storage. These are first party, are readable only by quorant.io, and are not transmitted to advertisers or any third party.
| Stored value | Purpose | Duration |
|---|---|---|
| quorant-lang | Remembers whether you chose the English or Korean interface | Until you clear it |
| quorant-user | Keeps you signed in between page loads | Until you sign out |
| quorant-runs | Displays your recent analysis history in your account | Until you sign out |
| quorant-promo | Holds a discount code you entered until checkout completes | Until you clear it |
| quorant-session | Sign-in token that unlocks your result files and support messages | Until you sign out |
| quorant-mp-notify | Remembers which notifications you turned on | Until you clear it |
| quorant-mp-archive | Keeps the list of projects you archived | Until you clear it |
| quorant-mp-team | Holds colleagues you invited to your account | Until you clear it |
| quorant-inapp-tried | Prevents the in app browser notice from repeating | Until the browser tab closes |
All of these are strictly necessary to deliver functions you have asked for, which is why the Site does not present a consent banner. You can delete them at any time through your browser's settings; if you do, you will be signed out and your language choice will reset.
The Site also loads two categories of resource from third parties: web fonts, and Google's sign in library. These providers receive your IP address as a normal consequence of serving the request. They do not set cookies on quorant.io.
Do Not Track. We do not track users across websites or over time, so a browser “Do Not Track” signal has no effect on what we collect, because there is nothing for it to switch off.
If we introduce analytics or advertising technologies in future, we will update this Policy and, where consent is required, obtain it before those technologies load.
We use the information described above to provide and secure the Services, to process payments, to respond to you, to meet our legal obligations and, where you have opted in, to send you occasional product news. Where the GDPR or UK GDPR applies, we rely on the following lawful bases.
| Purpose | Information used | Lawful basis |
|---|---|---|
| Creating and maintaining your account | Account information | Performance of a contract |
| Running the analysis you requested and delivering the outputs | Research Data | Performance of a contract |
| Expert review of a report by an assigned methodologist | Research Data | Performance of a contract |
| Processing subscriptions, invoices and refunds | Billing information | Performance of a contract; legal obligation |
| Responding to your questions and support requests | Communications | Legitimate interests; performance of a contract |
| Keeping the platform secure and preventing abuse | Operational information | Legitimate interests |
| Assessing applications to our programmes | Programme applications | Steps prior to a contract; consent |
| Sending product news and updates | Email address | Consent (withdrawable at any time) |
| Retaining accounting records | Billing information | Legal obligation |
Our legitimate interests are the secure and reliable operation of a paid research service. We do not rely on legitimate interests for marketing.
Access to uploaded files is limited to the people who need it to deliver your analysis: Quorant personnel operating the platform, and, where an expert verified report is included in your plan, the methodologist assigned to your run. Everyone with access is bound by confidentiality obligations.
We do not currently run an automatic deletion schedule for uploaded datasets. A file you upload remains in our storage until you or we delete it. You can ask us to delete a specific dataset, all of your uploads, or your entire account at any time by writing to contact@quorant.io, and we will act on that request as described in Section 9. If you are working under an ethics approval that requires deletion by a particular date, tell us and we will delete on that schedule.
We intend to introduce automatic deletion of raw uploads after delivery. When that is in place, this Policy will be updated to state the schedule, and registered users will be notified.
If you are an institutional customer and need a written data processing agreement, contact us and we will arrange one.
We do not sell personal information. We disclose it only in the circumstances below.
We rely on a small number of providers to operate the Services.
| Provider | What it handles | Primary location |
|---|---|---|
| Supabase | Database and file storage for uploaded datasets | United States |
| Netlify | Website hosting and serverless functions | United States |
| Stripe | Subscription billing, checkout and the customer billing portal | United States |
| Google Sign-In, and web fonts served to your browser | United States | |
| Notion | Hosted application forms for our programmes | United States |
| Contracted methodologists | Expert review of reports, where included in your plan | Canada and other countries |
This list is current as of the Effective Date. If you need it confirmed for a procurement or ethics review, contact us and we will provide it in writing.
Quorant operates from Canada and the providers listed in Section 5.1 are located primarily in the United States. If you use the Services from elsewhere, your information will be transferred to and stored in those countries, whose data protection laws may differ from those of your own.
We choose providers that offer data processing terms covering international transfers, and we are willing to enter into transfer safeguards required by your jurisdiction, including the European Commission's Standard Contractual Clauses or the UK International Data Transfer Addendum, on request. For users in the Republic of Korea, this Section together with Sections 1 and 5 constitutes notice of overseas transfer: the recipients, the purposes, the items transferred and the retention position are those described there.
We keep personal information for as long as it is needed for the purposes described in this Policy, and then delete it or irreversibly anonymise it.
Where we are required to retain a record for legal reasons, we restrict it so that it is no longer used for any operational purpose.
Quorant is not certified against ISO/IEC 27001, SOC 2 or any comparable standard, and we do not claim to be. We describe the measures we actually apply so you can assess them yourself. No security control is completely effective, and we cannot guarantee the security of information transmitted to us. You are responsible for keeping your account credentials confidential.
If we become aware of a breach affecting your personal information, we will contain it, notify affected users by email without undue delay, and notify supervisory authorities where the law requires it, within 72 hours of becoming aware where the GDPR applies. We will provide a written summary of cause, impact and corrective action on request.
Subject to the applicable law in your jurisdiction, you may ask us to:
To exercise any of these, email contact@quorant.io with “Privacy Inquiry” in the subject line, or use our contact page. We respond within 30 days. We may need to verify your identity before acting, and we may retain information where the law requires or permits us to.
Exercising a right never results in discriminatory treatment: we will not deny you the Services, charge a different price or provide a different quality of service because you made a request.
Quorant is the controller of the personal information described in this Policy, except for Research Data, where you are the controller and we act on your behalf. You have the right to lodge a complaint with your local supervisory authority, or with the Information Commissioner's Office in the United Kingdom. We do not use your information for automated decision-making that produces legal or similarly significant effects.
The Personal Information Protection and Electronic Documents Act applies to our handling of personal information. If you are not satisfied with our response to a privacy concern, you may complain to the Office of the Privacy Commissioner of Canada.
Where the Personal Information Protection Act applies, personal information is collected only for the purposes stated in this Policy. Section 6 constitutes notice of overseas transfer. Our designated privacy contact is:
| Privacy contact | Minkyu Kim, Founder & CEO |
|---|---|
| contact@quorant.io | |
| Location | City of Toronto, Ontario, Canada |
You may also report privacy concerns to the Personal Information Dispute Mediation Committee, the Korea Internet & Security Agency Privacy Complaint Centre, or the Personal Information Protection Commission.
We do not sell or share personal information as those terms are defined by the California Consumer Privacy Act as amended by the CPRA, and we have not done so in the preceding twelve months. We do not use or disclose sensitive personal information for purposes other than providing the Services. California residents may exercise the rights to know, delete, correct and limit by contacting us as described in Section 9. California Civil Code § 1798.83 additionally permits residents to request information about disclosures to third parties for direct marketing purposes; we make no such disclosures.
The Services are intended for researchers and professionals. They are not directed to children, and we do not knowingly collect personal information from anyone under 13. You must be at least 18 to enter into a paid subscription. Where the law of your country sets a higher minimum age for consenting to an online service, or requires the consent of a parent or legal guardian below a certain age, that higher standard applies instead of the ages stated here. If we learn that we have collected information from a child under 13 without appropriate consent, we will delete it. If you believe a child has provided us with information, contact contact@quorant.io.
The Site links to third party services, including Stripe for checkout and billing, Google for sign in, and hosted forms for programme applications. Your use of those services is governed by their own privacy policies, not by this one. We are not responsible for their practices, and we encourage you to read them.
This Policy is current as of the Effective Date stated at the top. We may update it as the Services change or as the law requires. Material changes will be announced on this page and, where they affect how we handle information you have already given us, by email to registered users before the change takes effect. Continued use of the Site or the Services after a change takes effect constitutes acceptance of the updated Policy.
We welcome questions and comments about this Policy or our privacy practices.
| Entity | Quorant |
|---|---|
| Privacy contact | contact@quorant.io (subject line “Privacy Inquiry”) |
| Responsible person | Minkyu Kim, Founder & CEO |
| Location | City of Toronto, Ontario, Canada |
| Response time | Within 30 days of a verified request |
If your procurement office or ethics committee needs written confirmation of how we handle data, or a data processing agreement, write to us and we will prepare it.
If the answer you need is not here, write to us. We reply within one business day.
Contact usIt depends on your analytical goal and the size of your data.
Basic — for researchers running foundational statistics on survey results: hypothesis testing, correlation, regression and clustering. Up to 10 MB per dataset.
Pro — for those writing journal articles or analytical reports. Covers structural equation modelling (CB-SEM), multilevel models, time series and survival analysis, with APA-formatted result tables, visualisation files and PDF reports. Up to 100 MB.
Smart — for researchers and organisations working with large datasets or advanced causal inference. Two expert verified reports a month and a dedicated point of contact. Up to 500 MB.
One count is deducted at the moment a deliverable is successfully generated from an uploaded dataset using the methodology you selected.
· Uploading a file or browsing methodologies does not deduct anything.
· We confirm with you that preprocessing has been done correctly before the analysis proceeds. If an error occurs during analysis because of a problem in the data, the count cannot be reversed.
Your remaining count resets to 100% automatically on each billing date. If you run out before then, you can upgrade to a higher plan and continue immediately.
Yes. You can change your plan freely at any time from your account page.
Whenever you cancel, you keep full access to every feature until the end of the period you have already paid for. Only the next automatic payment is cancelled.
Sign up with your institution's official email address. A discount code is sent to that address, usually within a few minutes and at most a few hours. The code is valid for 14 days from issue.
Separate from the automatically generated deliverables, it is a report in which a specialist personally reviews the analysis design and writes up the interpretation. It adds a step that re-checks the AI agent's output for errors, which is what makes it highly reliable. Smart includes two per month.
Statistical consulting is included with Smart once a month. It is most useful when you are unsure which methodology suits the data you want to analyse, and it gives you substantive feedback before you commit to an approach.
Based on your analysis results, we write a script covering how to interpret the findings in an actual presentation. Depending on the methodology it runs from one to six minutes of material, delivered as a Word or TXT file.
Yes. The rights to use the generated deliverables belong to you, and the output already matches journal submission formatting.
Spreadsheet formats — CSV, XLSX, XLS and TXT. PDF documents are also accepted for text mining and natural language processing.
Correct structure — variable names in the first row, and from the second row onward one observation per row: tabular data.
Cleaning tip — remove total and average rows, notes about missing values, and merged cells. Uploading pure data gives the most accurate result.
There is no need to worry if cleaning or variable coding is not finished. Request our data preprocessing add-on and a specialist will prepare the file so it is ready for analysis.
Recommended when
· reverse-coded survey items need handling, or variables need summing or recoding
· missing values need treatment, or outliers need diagnosis and removal
· merged cells, mixed text and numbers, or unnecessary rows and columns need tidying
· PDFs or unstructured documents need stopword cleaning for text mining and NLP
How to request — choose Data preprocessing support from the service list and submit your request. A specialist reviews the data structure and prepares it for immediate analysis.
The per-upload limits are 10 MB on Basic, 100 MB on Pro and 500 MB on Smart. There are two ways to resolve an oversized file.
Trim and compress — delete columns you will not analyse and any duplicated data, then upload.
Upgrade — move to Pro or Smart to raise the limit immediately.
The catalogue is organised into 23 detailed categories so you can narrow the choice down quickly. If it is still unclear after browsing, send the details of your research purpose, variables, measurement scales and data structure to analysis@quorant.io and we will recommend the most defensible method for your data.
One-to-one statistical consulting, in writing or by video call, is available on the Smart plan. On Smart, consultation covers the appropriate methodology, the analysis procedure and the expected turnaround.
Beyond the CSV files and visualisations the engine produces automatically, this is a tailored review written by a Quorant researcher.
Model adequacy review — whether the statistical model and assumptions you set are appropriate for the characteristics of your data.
Interpretation and writing guide — an detailed reading of the statistics you received, written so it can go straight into a paper or report.
A result that differs from your research hypothesis is not a computational error — it reflects the actual characteristics of the data. It therefore does not qualify for a rerun without deducting a count. In that situation an expert verified report is the better route: it gives you an academic and practical reading of why the result came out that way.
Yes, entirely. Every result table generated by Quorant follows the current APA notation, so it can be used as it is in a journal submission or a presentation without further formatting. All ownership and rights of use in the generated output belong to you.
No. You do not need to obtain an API key from an external service yourself. Analysis runs through the key Quorant issues, with no setup on your side.
The AI methodologies on the Smart plan can use up to roughly one million tokens — enough to work through large PDF documents or sizeable text datasets several times over using RAG.
Techniques that visualise the basis of an AI model's judgement, such as SHAP and LIME, are provided alongside the result. This addresses the black-box problem and gives you graphics that can be cited in a paper. Every computation is also verified to be identical to the reference libraries of the standard statistical packages.
On Smart, a Quorant partner researcher carries out a second review of the AI output and delivers it as an expert verified report.
Data is encrypted in transit and at rest and is held in a private storage bucket. Your data is never used for external AI model training or for another customer's analysis, and it is never shared. You can ask us to delete an upload, or all of your uploads, at any time. Quorant partner researchers are held to the same strict privacy standards — see the Privacy Policy page for details.
No, never. Quorant does not collect or retain research papers, confidential corporate data, survey text or any other data for the purpose of retraining AI.
For accurate statistical analysis and legal safety, we strongly recommend deidentifying any direct personal identifiers before uploading.
Delete identifiable fields such as names, phone numbers and email addresses, or replace them with random anonymous codes (for example ID_001, ID_002). Personal identifiers are not needed for numerical computation or AI analysis.
Pick the subject that fits and the form fills itself in. Most answers are already in the frequently asked questions
Quorant is not hiring in the usual sense. We are building a network of researchers who solve real analytical problems alongside us. Every week our members arrive with a dataset and a question they cannot answer alone. We would like you to help answer them.
You set the standard, publish alongside peers worldwide, and are paid properly for expertise you already have. Everything here is built on one idea: your name and your record grow with every project.
You are appointed to the examination board of the Quorant Certified Analytics Professional credential, writing and reviewing assessment items yourself. As a specialist in your field you help set the exam standards and the marking guidelines, shaping how the next generation is trained and how the discipline is standardised.
Join a network that stays in continuous contact with partner researchers across the world. Through collaboration with the platform community you can coauthor journal papers and technical articles, and build an international track record.
Compensation is paid per project — research advisory, data review and other assignments — at a competitive rate. Together we extend and refine the methodologies Quorant offers, creating new value as we go.
As a partner researcher your name and profile appear on the official site and in analysis reports, raising your visibility and credibility considerably. A distinctive record of research contribution in global data analytics is secured through official certificates and letters of reference — a powerful asset for your career.
The partnership is flexible enough to run alongside your main work, so you can take part in research projects or examination duties around your own schedule. By working on the projects that matter most, you stay ahead of market requirements and the latest technical currents.
Partner researcher applications are accepted all year round. If you have strong experience in quantitative analysis, we would be glad to hear from you.
Sign in or create an account to upload a dataset, request an analysis and track the methodologies you have used.
Tell me what you are trying to find out.
Describe your data the way you would say it out loud. I will work out which method fits, explain why, and tell you what your file needs to look like before we run it.
The panel gives a first read. A Quorant methodologist confirms the choice before the analysis runs.
Twenty-four specialists across basic statistics, advanced inference, big data and machine learning. Your question is routed to the one whose field it belongs to, and the reply explains why that method fits and what the common alternative gets wrong.
Researcher
Datasets are stored in a private bucket and deleted when you ask us to. Nothing is shared between accounts.
$39 per month
Invoices and receipts are issued by Stripe. Open the billing portal to download them or update your card.
Open billing portalThe interface follows the switch in the header. Consultation replies use the language you pick inside the chat.
Your datasets and results are removed and cannot be recovered. An active subscription is cancelled at the end of the current period.
Attach the file for analysis, provide a brief description of the data, and choose a methodology. All data is sent via an encrypted connection and stored in a private bucket. You can ask us to delete it at any time.
Your submissions will appear here with their status and deliverables.
| Run | Methodology | Dataset | Shape | Status | Submitted |
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A credential that shows you can choose the right methodology, read the output correctly and defend the result. Taken entirely online, from anywhere, at a time you choose.
Opening
September 20262026년 9월
오픈 예정
We are looking for graduate students who want to build the research ecosystem with us. This is not a marketing role. Ambassadors work alongside the Quorant methodology team on real studies, and the collaboration is the point.
This programme exists for collaboration, and everything else follows from that.
Applications are read by the methodology team, not by a recruiter. Write about the research, not about yourself.
The gap in research output between regions is not a gap in talent. It is a gap in tooling, funding and access. This programme exists to close part of that gap for researchers who are doing serious work with very little.
We do not publish applicants' research or claim any rights over it. Outputs belong entirely to you.
If cost is the only thing standing between you and the analysis, this programme is for you.
Quorant eliminates technical and administrative friction prior to data analysis, enabling researchers to focus entirely on their core ideas. We offer key supporting services that maximize analytical success, from data collection to preparation.
Reliable results begin with valid questions.
No matter how ground-breaking a research hypothesis is, flawed measurement tools inevitably distort the analysis. Quorant's partner researchers design survey items and measurement instruments with academic rigor, laying a solid foundation for your research.
Transforming raw, unstructured data into analysis-ready assets.
We handle the inefficient data cleaning process that typically consumes over 70% of research time. Raw data is refined into a seamless structure ready for immediate deployment into statistical algorithms.
Sign in to experience a completely effortless workflow.
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