15 Pre-College Statistics Programs for High School Students
Pre-college statistics programs for high school students provide an early introduction to data analysis, probability, and quantitative reasoning, offering pathways to data-driven business decision-making.
What do pre-college statistics programs involve?
These programs help you understand how statistical methods are used to interpret information, identify patterns, and make evidence-based decisions across fields like economics, public health, social sciences, and technology. They also offer a structured way to build foundational skills that are essential for college-level business coursework.
Why pursue pre-college statistics programs?
Participating in a pre-college statistics program allows you to work with actual datasets, learn statistical software, and explore how data informs research and policy. Many programs are offered by universities and are available in both in-person and online formats, making them accessible to a wide range of students.
To put your statistics skills to the test, you can consider participating in statistics competitions for high school students.
In this article, we highlight 15 pre-college statistics programs for high school students that focus on practical learning and academic preparation.
15 Pre-College Statistics Programs for High School Students
1. Carnegie Mellon Statistics and Data Science Camp
Location: Dietrich College of Humanities and Social Sciences, Pittsburgh, PA
Cost/Stipend: Free; students receive a bus pass and a stipend
Acceptance rate/cohort size: Selective
Dates: June 22–26
Application Deadline: March 15
Eligibility: High school students; preference to rising juniors and seniors; solid understanding of algebra is a plus
The Carnegie Mellon Statistics and Data Science Camp is designed as an introductory experience to statistics and data science. Through lectures and presentations, you'll explore fundamental concepts in data science, including data modeling, linear regression, and leveraging data with models and algorithms. You will receive an introduction to statistical computing and data visualization through daily computer labs covering the basics of R. The program introduces you to various pathways in the statistical field, along with field trips to witness data science in action.
2. Young Founders Lab
Location: This program is 100% virtual, with live, interactive workshops
Cost: Varies according to program. There is need-based financial aid.
Acceptance Rate/Cohort Size: Selective
Program Dates: Varies by the cohort
Application Deadline: There are 3 application deadlines that you can choose between; more details in the brochure!
Eligibility: Open to all high school students
The Young Founder’s Lab is a real-world start-up boot camp founded and run by Harvard entrepreneurs. In this program, you will work towards building a revenue-generating start-up that addresses a real-world problem, including a non-profit. You will also have the opportunity to be mentored by established entrepreneurs and professionals from Google, Microsoft, and X. Apart from building the start-up itself, you will also participate in interactive classes on business fundamentals and business ideation, statistical concepts and finance, and the use of data in making business decisions. You can check out the brochure for the program here.
3. Wharton Data Science Academy
Location: University of Pennsylvania, Philadelphia, PA
Cost/Stipend: $10,599
Acceptance rate/cohort size: Selective; approximately 75 students selected per term
Dates: Jun 21–Jul 11| Jul 12–Aug 1
Application Deadline: March 18
Eligibility: High school students currently enrolled in grades 10–11; strong background in math and coding; interest in data analytics and statistics
The data science academy is a rigorous 3-week program that builds an understanding of machine learning and data science through a statistical foundation and computational tools. Lectures will introduce foundational topics, including data wrangling, visualization, neural networks, large language models, and core modeling. The program includes hands-on learning through live demos and guided labs where you’ll work on cases and datasets through R, Python, and LLMs. Towards the end, you’ll work on a capstone project and live showcase, building a data solution to a challenge and presenting results. Apart from class, the academy offers enrichment through guest speakers, mentoring opportunities, office hours, and career guidance.
4. Ladder Internship Program
Location: Remote
Cost: Varies; Financial aid is available
Acceptance Rate/Cohort Size: Around 10%; 70-100 students
Dates: Multiple cohorts throughout the year
Application Deadline: Varies depending on the cohort
Eligibility: High school students who can work for 8-12 weeks
Ladder Internships is a selective start-up internship program for high school students interested in gaining experience with fast-growing start-ups. The start-ups offering internships span various fields, including finance, tech/deep tech, AI/ML, health tech, marketing, journalism, consulting, and more. Ladder’s start-ups are high-growth companies backed by Y Combinator and have raised an average of over $1 million in funding. The program includes one-on-one training in communication and time management, as well as group learning sessions with other interns. Interning at finance, accounting, and analysis firms helps you learn how statistical concepts are applied in work environments. Startups in the program are led by founders with experience at organizations like Google, Facebook, and Microsoft.
5. Harvard T.H. Chan School of Public Health StatStart
Location: Harvard T.H. Chan School of Public Health, Boston, MA
Cost/Stipend: Free; CharlieCard for commuting and lunch provided
Acceptance rate/cohort size: Competitive
Dates: One-month program in summer (exact dates not specified)
Application Deadline: Not specified
Eligibility: High school rising juniors or seniors; freshmen and sophomores eligible with preference to upper level; interest in STEM; basic algebra; designed for first-generation or low-income students, but all are welcome
StatStarts is an introductory statistics and R programming program that provides training in statistical programming and computational thinking. You will explore the fundamentals of statistical reasoning and probability concepts using real datasets through lectures and lab work. The program allows you to engage in structured problem-solving and interpreting outputs through lab work on R and collaborative research projects towards the end of the program. Outside of class, you will explore careers in data science, receive mentorship from biostatistics students, and gain guidance on the college application process.
6. University of Texas Research and Statistics Camp
Location: University of Texas at Austin, Austin, TX
Cost/Stipend: $2,700
Acceptance rate/cohort size: Selective
Dates: June 15–July 23
Application Deadline: Not specified
Eligibility: Students who will have graduated from 8th or 9th grade by summer; interested in university-level research; minimum grade requirements in math, science, and English (85 minimum, 80 allowed for advanced courses)
The Research & Statistics Camp serves as a five-day introductory program in statistics, along with hands-on work in modeling and analysis. You'll have the chance to work on an independent inquiry, supplemented by instruction in technical writing, research, inquiry, and statistics. During your inquiry, you'll be living on campus and receive project support from faculty and student mentors. The camp features other activities, such as lab tours, guest speakers, career exploration, and college guidance.
7. Quinnipiac University Data Sciences Lab
Location: Data Sciences Lab, Quinnipiac University, Hamden, CT
Cost/Stipend: $3,600 residential option; $2,600 commuter option
Acceptance rate/cohort size: Selective
Dates: July 6–17
Application Deadline: Not specified
Eligibility: Current high school students; interest in problem-solving and foundational data science concepts
Data Science Lab offers an in-depth exploration of data at the intersection of statistics, math, and computer programming. Over the 2-week program, you’ll understand how data is leveraged in multidisciplinary fields, including business, public policy, healthcare, and technology. Through lectures and presentations, you’ll explore concepts in algorithms, data visualizations, probability and statistics, data ethics, machine learning, and bioinformatics. You’ll engage in hands-on learning by analyzing data sets, looking into case studies, and working on projects accompanying modules. The experience culminates in a poster session where you will share your experience over the program.
8. Washington University in St. Louis Introduction to Statistics
Location: Washington University in St. Louis, St. Louis, MO
Cost/Stipend: Commuter $4,075 for one course; residential $8,385 for one course; residential $12,135 for two courses
Acceptance rate/cohort size: Selective
Dates: June 7–July 11
Application Deadline: April 1
Eligibility: Current junior in high school; academically motivated students enrolled in a challenging curriculum
Washington University offers a five-week introductory statistics program for high school students. Modeled on a college-level curriculum, the program offers an in-depth exploration of foundational data science and statistics concepts. Through a mix of lectures and hands-on work, you will be introduced to concepts including data collection, designing experiments,, consumer price index, inference, elementary probability, and hypothesis testing. During the program, you have the option to live on campus to experience college life while also earning college credit.
9. Syracuse University Data Visualization and Analysis
Location: Syracuse University, Syracuse, NY
Cost/Stipend: Residential $2,795; commuter $2,309
Acceptance rate/cohort size: Selective
Dates: July 19–24
Application Deadline: Not specified
Eligibility: Rising high school sophomores, juniors, seniors, or high school graduates
Syracuse University offers a hands-on course in data visualization and analysis, using tools such as Excel and Tableau. The course features workshop-style classes that cover the entire data collection process, including cleanup and basic statistics to generate insights and present to stakeholders. You will engage in hands-on work, learning how to visualize data, generate insights, and work with tools like Tableau, where you will learn about design principles. In addition to classes, you will live on campus and participate in group activities and lab work.
10. UChicago Introductory Statistical Methods and Applications for the Social Sciences
Location: Virtual
Cost/Stipend: $4,980
Acceptance rate/cohort size: Moderate
Dates: June 15–July 2
Application Deadline: Not specified
Eligibility: High school 11th graders; high school 12th graders; undergraduates
This course dives into the application of fundamental data and statistical concepts in the context of social and behavioral sciences. The course provides a holistic guide on taking raw data and converting it into insight using statistical reasoning, visualization, and tools like R. You’ll understand statistical procedures used in social research, including simple linear regression, bivariate correlation, z-test, multiple regression, and t-test. You’ll work with data sets to gain insight into organizing data, sampling distribution, statistical techniques, hypothesis testing, and analysis using tools.
11. Brown Pre-College Programs: Summer@Brown (Statistics Course Option)
Location: Brown University, Providence, RI, with virtual options available
Cost/Stipend: Varies by course
Acceptance rate/cohort size: Selective
Dates: Varies by course
Application Deadline: Not specified
Eligibility: Rising sophomores, rising juniors, rising seniors, between the ages of 14 and 18
Brown University offers residential summer courses that allow exploration of various subjects that are modeled on Brown’s undergraduate curriculum. Statistics and data science courses offered explore applications within biomedicine, public health, research, epidemiology, machine learning, algorithms, and the environment, among others. The courses provide an understanding of key statistical concepts, including distributions, probability, and hypothesis testing, across different contexts. You’ll engage in collaborative projects, interactive sessions, group discussions, and guidance from your instructor.
12. Cornell PreCollege Studies (Statistics Course Option)
Location: Virtual
Cost/Stipend: Varies based on course
Acceptance rate/cohort size: Selective
Dates: Typically between June and July (for the three- and six-week summer sessions)
Application Deadline: Varies based on the course
Eligibility: High school students (typically rising juniors and seniors; courses designed for motivated advanced learners)
Cornell University allows you to earn real college credit while taking university courses taught by Cornell faculty. By taking up a data science and statistics-aligned course, you’ll cover data exploration, visualization, data gathering, probability, and statistical inference methods while working with real data sets. You’ll learn how to use statistical software tools and simulation tools and work with real-world data from a variety of disciplines.
13. Bentley University Analytics Academy
Location: Bentley University, Waltham, MA
Cost/Stipend: Not specified
Acceptance rate/cohort size: Selective
Dates: Session B: June 16–20; Session C: June 23–27; Session E: July 7–11 (multiple one-week sessions)
Application Deadline: Not specified
Eligibility: Rising high school juniors and rising high school seniors interested in data analytics and data science concepts
The Analytics Academy is a five-day program that introduces fundamental data science concepts along with their application in varied career pathways. Some topics you’ll encounter during the program include correlation, visualizations, data pitfalls, data ethics, and storytelling, among others. You’ll engage in hands-on learning by working with tools like Tableau, analyzing datasets, and creating visualizations. Besides class work, you’ll engage in sessions with guest speakers and gain insight into different pathways within data science and analytics. The program ends with a capstone project where you’ll put what you’ve learned into practice.
14. UNC Charlotte C-STEM Center Saturday Data Science Academy
Location: Saturday Data Science Academy, Center for Science, Technology, Engineering and Mathematics Education (C-STEM), University of North Carolina at Charlotte, Charlotte, NC
Cost/Stipend: $125
Acceptance rate/cohort size: Selective; typically 25 students per cohort
Dates: Weekly sessions that run between January and April (exact dates not specified)
Application Deadline: January 9
Eligibility: High school students in grades 9–12 interested in foundational data science and data analysis
The Saturday Data Science Academy is an immersive weekly program that combines lectures, presentations, and activities to deliver key data science concepts and applications. Topics covered include statistical methods, data visualization, data analysis, and machine learning. You’ll work with data sets and case studies, helping you understand real applications while also working on critical thinking and analytical skills. The academy invites data science professionals to share their experiences and provide guidance on opportunities in the field. During the program, you’ll build a portfolio of projects and experiences, which you’ll get to showcase at the end of the program.
15. Lewis and Clark College Data in Action: Sustainability, Science, and Storytelling
Location: Lewis & Clark College, Portland, OR
Cost/Stipend: $1,800
Acceptance rate/cohort size: Selective
Dates: July 12–17
Application Deadline: January 1
Eligibility: Rising high school students (grades 9–12) passionate about sustainability, data science, and data storytelling
The data in action program offers an exploration of data science at the intersection of journalism, sustainability, and the environment. Over 6 days, you’ll understand the tools and techniques to create data-driven stories while working with environmental data sets. You’ll learn how to work with tools used for data analysis and visualization through projects, workshops, and field trips. The program introduces you to working journalists who will guide you through the process of storytelling, effective data presentation, and building proper workflows. By the end of the program, you’ll have produced your own piece of data journalism centered around sustainability.