2 Days
·Cohort-based Course
Apply the best algorithms to your dataset to get significant conclusions and customize the visualizations for your paper submission.
2 Days
·Cohort-based Course
Apply the best algorithms to your dataset to get significant conclusions and customize the visualizations for your paper submission.
Hosted by
Jesús López
Statistical Programmer Consultant | +100 PhDs Statistical Analysis Programmed
Course overview
A personalized training experience to identify the bad habits in programming that hold you back from finishing your projects and explain the best practices that will put you back on track to finish them.
Based on vast experience working with PhDs, we've designed a program with exercises that will help you solve the main issues you face while programming the stats of your papers.
01
You get frustrated repeatedly by asking Google and ChatGPT the same questions and getting confused about what you know and don't.
02
You lack the statistical intuition to interpret the results and the programming skills to visualize them concisely for paper submission.
03
You've got scripts everywhere, costing you valuable time whenever you want to reuse them. Instead, refactor for single script execution.
Hands-on training
Learn through practice, not theoretical slides that induce you to assume you know what you don't; therefore, you get lost when it's time to program on your own.
Single script (template) to simulate statistical reports based on multiple conditions
Create a versatile script template to generate reports under different conditions, allowing precise benchmarking and replication.
Data visualizations personalized for paper submission
Learn to craft customized data visualizations for academic publications, enhancing the clarity and impact of your findings.
Intuition to determine which are the best algorithms to achieve the conclusions you need
Master selecting and applying the best statistical algorithms for robust and reliable conclusions.
Programming discipline to reason the code instead of copy-pasting by memorization
Understand coding principles and best practices to write clear, efficient, and maintainable code, reducing dependency on ad-hoc solutions.
Confidence in your statistical knowledge to discuss with peers
Gain the assurance to effectively communicate and defend your statistical analyses in academic discussions and peer reviews.
3 interactive live sessions
Lifetime access to course materials
30 in-depth lessons
Direct access to instructor
Projects to apply learnings
Guided feedback & reflection
Private community of peers
Course certificate upon completion
Maven Satisfaction Guarantee
This course is backed by Maven’s guarantee. You can receive a full refund within 14 days after the course ends, provided you meet the completion criteria in our refund policy.
Statistical Programming for Academic Projects
Jul
18
Jul
19
Jul
20
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