R for Statistical Analysis and Research Corporate Training
Build statistical analysis expertise with instructor-led R training for your teams.
This instructor-led program takes your team from R foundations to complete, reproducible research studies. Through guided labs on realistic datasets, your team practices modeling, visualization, and reporting skills they use every day.
Instructor-led group trainingVirtual / on-site / off-site10 languagesDelivered inEnglish, Spanish, Mandarin, German, Arabic, Portuguese, Hindi, French, Japanese, Italian100+ countriesWe have delivered inUnited States, United Kingdom, India, Canada, Germany, France, Netherlands, UAE, Saudi Arabia, Singapore, Australia, Japan, Brazil, South Africa and 90+ more countries
How we build an analysis-driven research team
The Edstellar R FOR STATISTICAL ANALYSIS & RESEARCH Capability Model
Diagnose analysis skill gaps
We assess how your team analyzes data and reports findings today.
Standardize reproducible workflows
We set shared practices for scripted, versioned, reviewable analysis.
Practice in guided labs
Your team practices modeling and visualization in instructor-led hands-on labs.
Measure analysis quality
We track modeling accuracy, visual clarity, and reproducibility across modules.
Scale analytics org-wide
Playbooks and cohort sequencing spread sound analysis practices to every team.
Need more than one program?Get a group quote
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Program Overview: What is R for Statistical Analysis and Research?
R for Statistical Analysis & Research is an instructor-led program for analysts and researchers moving from spreadsheets to rigorous statistics. Participants learn R programming, data wrangling, statistical modeling, visualization, and the reproducible workflows that make research reviewable. The path runs from raw data to trusted findings, with every technique practiced on realistic datasets.
Across six modules and 24 hours, participants move from R foundations and data cleaning through modeling, visualization, reproducible workflows, and a capstone research study. Every module pairs instructor-led learning with guided labs, so skills are practiced in real analysis scenarios rather than presented in slides. Instructors coach teams through debugging, model selection, and interpretation, reviewing each analysis. The program closes with a capstone where each team completes an end-to-end research study.
Teams without reproducible habits drown in one-off spreadsheets: numbers nobody can reproduce, models nobody documented, findings that collapse under review. The cost shows up in rejected papers, failed audits, and decisions built on shaky analysis. This program replaces ad-hoc habits with scripted workflows, so every result traces back to its data and code.
The capstone is an End-to-End Research Study. Each team takes a raw, messy dataset, cleans it, builds and validates statistical models, creates publication-quality visualizations, and writes up the findings in a fully reproducible R workflow. Instructors review the study for statistical soundness and reproducibility, as a peer reviewer would. The team keeps the complete study as a template: the next analysis they run starts from a proven, reviewable process instead of a blank script.
Across six modules, participants move from R foundations and data cleaning through modeling, visualization, reproducible workflows, and a capstone research study. Every module pairs instructor-led learning with guided labs on realistic datasets, so skills are practiced in real analysis scenarios, not just presented in slides.
What's Included in this Workshop for Your Enterprise Teams
- 1
R foundations and wrangling
Load, clean, and shape data for analysis.
- 2
Statistical modeling
Fit models and interpret results with diagnostics.
- 3
Visualization
Build honest charts that communicate findings.
- 4
Reproducible workflows
Version and review analysis like software.
- 5
Capstone study
Deliver a complete, reviewable research study.
- Instructor-led sessions in hybrid, onsite, or live virtual formats
- Guided hands-on labs for every module
- Lab guides, R code templates, and reference materials
- Pre-training skills assessment for your cohort
- Capstone study review with instructor feedback
- Post-training support for rollout questions
Build your team's skills. Anywhere in the world.
Real-world use cases
from day one
Instructor-led training
for your teams
Delivered globally
in 100+ countries
Enterprise Training Solutions Customized for Your Company
One partner for instructor-led corporate training, delivered the way your teams work.
Request a Training Quote- Customized Training Delivery
- Scale Your Training: Small to Large Teams
- In-person Onsite, Live Virtual or Hybrid Training Modes
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- Hands-On Labs on Live Infrastructure, Led by Industry Experts
R for Statistical Analysis and Research Course Topics and Program Outline
A six-module program that takes your team from R foundations to a complete, reproducible research study.
Built by Edstellar with data science and statistical research practitioners
Built by data professionals who run real analyses in production, shaped around your team's data and research domain.
We review your team's current analysis practices to find the gaps this R program will close.
Your team learns R fundamentals and data wrangling through instructor-led sessions and live demos.
Guided labs let your team practice modeling and visualization on realistic datasets in safe settings.
Your team builds reproducible workflows and delivers a complete, reviewable research study.
Outcome: a complete research study your team analyzed, validated, and reported with reproducible R code.
Delivered as
The program runs in hybrid, onsite, or live virtual formats with instructor-led sessions and guided labs throughout.
Set up a reproducible R project and load a practice dataset.
learna)R syntax, data types, and functions
b)Project setup with a scripted workflow
c)Reading and writing common data files
d)Packages and environment management
Clean a messy business dataset into an analysis-ready table.
learna)Filtering, selecting, and arranging rows
b)Joining multiple data sources
c)Reshaping data between wide and long forms
d)Handling missing and messy values
Fit regression models on a practice dataset and check diagnostics.
practicea)Linear regression and interpretation
b)Comparing groups with standard tests
c)Model diagnostics and assumptions
d)Communicating model results clearly
Produce a set of publication-quality charts from analysis output.
practicea)Exploratory plotting for insight
b)Grammar of graphics for custom charts
c)Designing honest, readable visuals
d)Sharing plots and reports with stakeholders
Convert a notebook-style analysis into a versioned, reproducible report.
applya)Scripted reports that regenerate cleanly
b)Version control for analysis projects
c)Code review and quality checks for scripts
d)Packaging results for peer review
Deliver a complete analyzed study with reproducible code and findings.
applya)Framing the research question
b)Analysis plan and execution
c)Validation and sensitivity checks
d)Findings presentation and review
Customize this program tailored to your team?
Tell us your training needs: what your team already works with, the level they’re at, and the topics you want them to focus on. We’ll adjust the modules, duration and hands-on labs, and send you a customized outline for your group.
Key Skills and Outcomes Your Team Will Gain
By the end of the program, your team will analyze data, validate findings, and report results with reproducible R workflows.
R programming fundamentals
Write clean R scripts, manage projects, and work confidently with the R ecosystem.
Data wrangling and cleaning
Transform raw, messy data into reliable analysis-ready datasets.
Statistical modeling
Fit and interpret regression models and standard tests with proper diagnostics.
Data visualization
Create clear, honest charts that communicate findings to any audience.
Reproducible analysis workflows
Build scripted, version-controlled analyses that regenerate and can be reviewed.
Code quality for analysis
Apply review and quality practices so analysis code stays trustworthy and maintainable.
Research reporting
Present methods and findings in structured reports ready for stakeholders or peer review.
Teams that Benefit from this R for Statistical Analysis and Research Group Training
This program is built for analytics, research, engineering, and BI teams that turn data into decisions. Content adapts to each role and experience level, so every cohort practices the workflows it owns.
Standardize analysis on reproducible R workflows
Analysts move from ad hoc spreadsheets to scripted R workflows that colleagues can rerun and trust.
Workflow friction
- Spreadsheets hide errors
- Analysis cannot be rerun
- Methods lack documentation
How the program helps
- Repeatable analysis pipelines
- Clearer stakeholder reports
- Faster insight turnaround
Practice use cases
- wrangling labs
- modeling sprints
- report automation
Run rigorous, reviewable studies
Researchers adopt reproducible practices so every study is transparent, validated, and ready for peer review.
Workflow friction
- Methods are hard to reproduce
- Validation steps get skipped
- Reports take too long
How the program helps
- Transparent methodology
- Validated study results
- Review-ready reporting
Practice use cases
- study design
- validation checks
- findings reviews
Bring code quality to data science
Engineers apply version control, testing, and review practices to analytical codebases.
Workflow friction
- Analysis code is fragile
- No review process exists
- Pipelines break silently
How the program helps
- Versioned analysis code
- Reviewed, tested scripts
- Reliable data pipelines
Practice use cases
- git workflows
- code review
- pipeline labs
Deliver trusted dashboards and metrics
BI teams build the visualization and reporting skills that turn analysis into decisions.
Workflow friction
- Charts mislead stakeholders
- Metrics differ by team
- Reports arrive late
How the program helps
- Honest, clear visuals
- Consistent metric definitions
- Self-serve reporting
Practice use cases
- visualization labs
- metric design
- dashboard reviews
Cohorts can mix these functions or focus on one team; labs scale to the datasets your team analyzes.
Prerequisites: This program benefits analysts, researchers, engineers, and BI professionals at any experience level. Basic spreadsheet comfort helps but is not required, and no prior R or statistics background is needed. The program adapts to your team's data and research domain.
Data Analyst to Research Lead
The path follows the program: R and wrangling at Foundation, modeling and visualization at Intermediate, reproducible workflows and study leadership at Advanced and Very Advanced.
A learning path that grows with analytics careers, from R basics to confident, reviewable research delivery.
Mixed cohort, or several teams at once?
We can tailor the training to different teams, roles, and experience levels within the same program.
Certificate of Training Completion.
On successful completion, employees receive an Edstellar course completion certificate, recognizing their commitment to ongoing learning and professional development. It validates the skills they have built and motivates them to keep growing and contribute to organizational success.
Earned, not attended. Awarded on completion of all hands-on labs and the capstone project.
Training Delivery Modes: Virtual, Onsite and Hybrid
Choose the format that fits your team's location and schedule. Every mode includes the same instructor-led curriculum and guided labs.
Hybrid Training
Combine onsite collaboration with virtual flexibility. Your team meets in person for key sessions and joins labs online.
- In-person sessions for modeling workshops
- Virtual guided labs with live instructor support
- Flexible scheduling across time zones
- Same curriculum as onsite and virtual
Onsite Training
The instructor delivers the full program at your location, with labs built around your team's datasets.
- Full program delivered at your office
- Labs using your team's real-style data
- Direct access to the instructor all week
- Ideal for co-located analytics teams
Live Virtual Training
Live online sessions with breakout labs give distributed teams the full hands-on program from anywhere.
- Live instructor-led online sessions
- Breakout rooms for guided lab work
- Digital materials and lab environments
- Recorded sessions for review
Need a training format that works for your team?
Full days, half days across weeks, or split by module. Tell us the delivery window and we schedule the cohort around it.
Frequently Asked Questions
Share your team size and timelines with us and we will send a tailored quote within one business day.
Yes. A short call with a training advisor helps us map the program to your team's goals before you commit.
Yes. The program runs live online with an instructor, breakout labs, and the same hands-on curriculum as onsite.
Yes. Onsite delivery brings the instructor and guided labs to your location for your whole team.
The instructor-led program runs 24 hours across six modules, scheduled to fit your team's working days.
Question not answered here?
Put it in the request. A training specialist answers it directly, within one business day.
Where this Training Fits in Your Team's learning path.
R for statistical analysis sits second, after business statistics. Your team needs the statistical ideas first, then R gives them a reliable way to apply them to real data. From there the path widens into data science in R and finally into predictive analytics and forecasting.
Why Choose Edstellar as Your R for Statistical Analysis and Research Corporate Training Provider
Edstellar delivers instructor-led R training that turns analysis learning into reproducible, reviewable research.
EXPERT TRAINERS
YEARS DELIVERING
ORGANIZATIONS TRAINED
CERTIFIED
Tailored
The program adapts to your team's data, research domain, and tooling so every lab mirrors your real analysis work.
Proven Methodology
A structured learn-practice-apply arc takes your team from R basics to a validated, reviewable research study.
Practice-Based Learning
Your team analyzes realistic datasets in guided labs instead of just watching statistical concepts presented.
Expert Trainers
Instructors are practicing data professionals who run real analyses and mentor analytics teams daily.
Global Scale
We deliver consistent instructor-led training across time zones for distributed analytics and research teams.
Measurable Outcomes
Skills assessments and a capstone review show exactly how far your team's analysis capability advanced.
Develop Reproducible R Research With Checked Data, Model Diagnostics, and Clear Findings
Edstellar helps analysts and researchers build a reviewable path from raw data to findings in R. Participants clean datasets, fit statistical models, and create explanatory visuals before organizing a reproducible report. The final study is assessed for preparation transparency, diagnostic reasoning, code consistency, and conclusions proportionate to the analytical evidence.
- Step 01
Consult
We explore spreadsheet comfort, research questions, and statistical experience to identify support needed for R programming, data cleaning, modeling, or reproducible reporting.
- Step 02
Plan
We establish the R project and data foundations before wrangling, regression modeling, and visualization, then consolidate code and findings into the reproducible research study.
- Step 03
Align
We align statistical analysis and R expertise with participant research domains, providing foundational explanations where programming or statistical methods are new to the cohort.
- Step 04
Customize
We adapt sample research and business datasets to familiar analytical questions, retaining messy records and model-diagnostic issues that require documented decisions rather than hidden cleanup.
- Step 05
Execute
Participants prepare tables, fit regressions, and build report visuals, receiving feedback on cleaning choices, diagnostic interpretation, code organization, and the relationship between findings and evidence.
- Step 06
Evaluate
We assess the research study for reproducible code, transparent preparation steps, appropriately checked models, and clearly communicated findings that acknowledge the analysis's limitations.
Also from Edstellar
Talent assessments
Psychometric, behavioral, leadership and 360-degree assessment.
→Training needs analysis
Needs analysis, gap identification, and a training roadmap.
→L&D consulting
Learning strategy, content, technology and ROI measurement.
→OD consulting
Org design, succession planning and cultural change.
→Managed training services
Training outsourcing, vendor management, logistics and administration.
→Coaching solutions
Executive and manager coaching that keeps skills in use.
Start an RFP shaped to your needs.
Answer three quick questions about team size, scope, and how often you need the program run, then send the request from the last step. Everything you choose travels with it, so you only fill this in once.
How many team members need training?
R for Statistical Analysis & Research Training Training Packages & Pricing
Where L&D holds an annual budget, license packages price the whole year at once instead of raising a purchase order per workshop. Hours and licenses are pooled across teams, programs and locations, so unused capacity is not stranded in one department.
Starter
120
trainee licenses64 hours of group training
Tailored for SMBs
Growth
320
trainee licenses160 hours of group training
Ideal for growing SMBs
Enterprise
800
trainee licenses400 hours of group training
Designed for large corporations
Custom
Unlimited
trainee licensesDuration set by the rollout
Multi-region and multi-year
Training Packages & Pricing
Choose the training format that works for your team. Pricing is customized based on your requirements, cohort size, and delivery needs.
Request R for Statistical Analysis and Research Training for Your Team
Tell us about your team and goals, and we will tailor the R for Statistical Analysis & Research program to your data and research domain.