Find your Course
Explore our curated database of people analytics courses from government-accredited institutions. Whether you’re just starting out or looking to deepen your expertise, you’ll find high-quality learning opportunities from trusted providers.
Detailed page for HCM Introduction to Statistics
Course/Program: Quick Facts
- Official name: HCM Introduction to Statistics
- Year first launched: 2022
- Affiliated with an accredited university: Yes, with New York University, School of Professional Studies
- Website: https://www.sps.nyu.edu/professional-pathways/certificates/human-capital-management/people-analytics/HRMD1-CE1003-hcm-introduction-to-statistics.html
Course/Program Details
- Target Audience: HR Professionals
- Proficiency Level: Beginner/Foundational, Intermediate
- Delivery Format: Online Instructor-Led
- Typical Completion Time: 1-2 months
- Hours Instruction / Coursework per Week:
- Number of Students Completed the Program: 51-200
Certification & Cost
- Credential upon Completion:No formal credential
- Pricing Structure: One-time payment ~ Total Cost (USD): $501-$1,000
- Are scholarships or financial assistance available: No
Course Description
In this course, students will gain a foundation in what is called “model thinking” (i.e., the art of exploring the statistical properties of a dataset so as to choose the most appropriate statistical model). The course will start with statistical first moments—means, medians, and distributions—so that the students all have a strong foundation in the basics. Then, it will gradually move up to statistical inference—which is about deriving modeled estimates and testing the soundness of one statistic versus another. In an effort to make the material more engaging and real-world applicable, the course will be taught, primarily, through R programming (a free, open-source programming language, most famously used for statistical analysis.
- Primary Topics Covered: HR Data Management, HR Metrics and KPIs, Statistical Analysis for HR, Predictive Workforce Analytics, Performance Analytics
- Software/tools used:
- Notable instructors or contributors:
Additional Information
- Hands-on projects or capstone experiences:
- Is this course/program eligible for continuing education credits or professional certifications:
