15 Statistics Courses for High School Students
If you’re a high school student interested in statistics, the subject has broad applications across fields such as data science, public health, governance, and analytics. Studying statistics will allow you to analyse data, identify patterns, and make informed decisions, helping across academic projects, college applications, or even your next venture.
What do statistics courses involve?
Statistics courses help you build a fundamental understanding of the field by exploring topics such as probability theory, statistical inference, and data analysis. You'll also get to work with tools like Python, R, and Tableau. The courses offer practice through projects, helping you build quantitative reasoning skills and learn to use data storytelling and visualisation to communicate your findings.
Why pursue statistics courses as a high school student?
Pursuing statistics courses in high school helps you build strong analytical and data interpretation skills that are valuable across many careers. You learn how to understand patterns, make predictions, and draw meaningful conclusions from data. Many of these courses offer the opportunity to explore various pathways in statistics and data science, receive mentorship, and network with professionals in the field.
To put your statistics skills to the test, you can consider participating in statistics competitions for high school students.
While there are many courses out there, we have narrowed down a list of the top 15 statistics courses for high school students.
15 Statistics Courses for High School Students
1. Wharton Global Youth Program Introduction to Statistics and Data Science
Location: Virtual
Cost/Stipend: $4,230
Acceptance rate/cohort size: Selective
Dates: Varies sessions offered throughout the year
Application Deadline: Varies by session
Eligibility: High school juniors and seniors
The introduction to statistics and data science offers an exploration of statistics with a focus on application through tools such as Python and R. During the course, you will learn how to apply statistical thinking to real-life scenarios, such as business problems. You will also learn about applications in various industries. The course structure covers basic statistical concepts, including variance, hypothesis testing, the mean, and quantiles. You will work on projects that involve using programming languages to analyse datasets, extract insights, and apply management principles.
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
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 starting a revenue-generating start-up that addresses a real-world problem, which can include building a non-profit. Throughout the program, you'll be mentored by established entrepreneurs and professionals from companies such as 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. Harvard Pre-College Summer Program (Statistics Course Option)
Location: Harvard University campus, Cambridge, MA
Cost/Stipend: $6,100 with a $75 application fee
Acceptance rate/cohort size: Selective
Dates: Session I: June 21–July 2; Session II: July 5–17; Session III: July 19–31
Application Deadline: February 22
Eligibility: Rising high school juniors and seniors (must be at least 16 by program start)
Harvard pre-college program offers an in-depth exploration of a subject of your choice, along with a glimpse of college life. The program runs over 2 weeks and will delve into a specific subject with other passionate peers. You have the option to choose between various statistics courses in the context of data science, public health, ecology, among others. The courses are designed to help you use various observational and quantitative techniques to work with data sets in a relevant field. You will also learn practical application by working with software art and by practicing with published and simulated datasets.
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 that places high school students with fast-growing startups across a range of industries. The start-ups offering internships span various fields, including finance, tech/deep tech, AI/ML, health tech, marketing, journalism, and consulting. Ladder’s start-ups are high-growth companies backed by Y Combinator and have raised an average of over $1 million in funding. Beyond your placement, 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 often led by founders with experience at organizations such as Google, Facebook, and Microsoft.
5. 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 in St. Louis offers an introductory statistics course that runs for five weeks in the summer. During the program, you will develop a fundamental understanding of statistics by learning about topics such as data collection, organization, and inference. You'll work on projects and practical applications by designing experiments and focusing on data visualization, such as graphs and tables. The program focuses on statistical inference, where you will gain insight into elementary probability and hypothesis testing.
6. 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
The data visualization and analysis course offers a practical introduction in which you’ll work with raw data, understand how it's captured, and summarize and visualize it to generate insights. The course takes place over one week, during which you will learn to work with datasets, explore and generate insights, and use storytelling methods to communicate findings effectively. You’ll work on practical application by working with tools such as Microsoft Excel and Tableau, where you will learn design principles and data visualization methods. The program culminates in a showcase where you will work with a dataset and present your findings to stakeholders to inform their decisions.
7. 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
The University of Chicago offers an introductory course in statistical applications with a focus on the social sciences. During the course, you will work with social and behavioral science-related data and learn how to apply statistical concepts, principles, and procedures to gather insights and prepare findings. You will explore fundamental statistical concepts, including normal distribution, hypothesis testing, and sampling distribution, and use R for the practical application of these techniques. The course is designed to help you apply statistical description and inference to applied research in social sciences by using appropriate procedures to collect data, use hypothesis testing, and communicate your findings effectively.
8. 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 pre-college studies allows you to delve into subjects through experiencing college-level curriculum, where you can explore potential majors and develop study skills, while earning college credit and receiving a Cornell transcript. Cornell offers a range of statistics courses across biology, social science, data science, and statistical science. These courses help you explore foundational topics and statistics, including data summarization, visualization, sampling, and statistical inference. You will also gain practical experience by learning the basics of R programming and applying statistical inference to datasets in your field.
9. 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
Summer@Brown is a summer program where you’ll explore a subject you’re interested in through college-level academics. You'll be taught by instructors and offered collaborative activities to help you practice what you've learned. Brown offers a range of statistics courses, including introductory and field-relevant courses, with a focus on machine learning, public health research, and biomedical discovery. These courses help you explore key statistical concepts, including correlations, regression models, probability distributions, and statistical significance, through practical examples and real-world datasets. You will learn how to gather insights and use statistical methods in various fields by focusing on real problems.
10. UCLA Summer Sessions (Statistics Course Option)
Location: UCLA Summer Sessions, University of California, Los Angeles, CA (virtual options available)
Cost/Stipend: Varies by course
Acceptance rate/cohort size: Selective
Dates: Courses take place in the summer (exact dates vary)
Application Deadline: Varies by course
Eligibility: High school students
UCLA offers summer sessions where high school students delve into a subject alongside other passionate peers. The courses incorporate co-curricular components and practical experience through hands-on projects, field trips, and guest lectures. The statistics course options provide a foundational overview of statistical concepts, including statistical reasoning, probability, statistical programming, linear models, and data analysis. You will gain hands-on experience in statistical programming by working with the software R and also dive into the design and analysis of experiments.
11. UC Berkeley Summer Sessions (Statistics Course Option)
Location: UC Berkeley Summer Sessions, University of California, Berkeley, Berkeley, CA (virtual options available)
Cost/Stipend: Tuition varies by course/units
Acceptance rate/cohort size: Selective
Dates: Multiple sessions offered throughout the year
Application Deadline: Typically early summer; specific date varies by session track
Eligibility: High school students
Berkeley summer sessions offer high school students the opportunity to study university-level courses while earning an official Berkeley transcript. These courses take place over the summer, where you will delve deeper into a subject, understand fundamental concepts, and learn through projects guided by Berkeley instructors. The statistics course options you can choose from delve into fundamental topics, including variables, regression, probability, sampling, approximation, and interval estimation. The statistics course options offered include courses with a focus on business and public health.
12. University of Michigan High School Placement in STATS & Data Science Courses
Location: Department of Statistics, College of LSA, University of Michigan, Ann Arbor, MI
Cost/Stipend: Tuition-based (varies by course)
Acceptance rate/cohort size: Selective
Dates: Academic year and summer options
Application Deadline: Varies by course
Eligibility: High school students seeking placement in university-level statistics/data science courses
The Statistics Department of the University of Michigan offers a placement program for high school students interested in enrolling in statistics and data science courses. The statistics courses that you can enroll in cover fundamental topics in the context of various current events and media stories. You can also study statistics with a focus on biology, public health, mathematics, and experimental design. The courses are offered to students who already have a foundational understanding of advanced mathematics and have scored 4 or 5 on AP Calculus. If you don't have this level of mathematical preparation, you should have at least taken AP Statistics to be eligible.
13. Quinnipiac University: Data Sciences Lab
Location: Data Sciences Lab, Quinnipiac University, Hamden, CT
Cost/Stipend: $3,600 residential; $2,600 commuter
Acceptance rate/cohort size: Selective
Dates: July 6–17
Application Deadline: Not specified
Eligibility: High school students interested in data science and problem-solving
The Data Science Lab is designed for students interested in problem-solving and applying technology to real-world challenges. During the program, you will delve into mathematics, statistics, and computer programming, learning to analyze datasets, identify issues, and derive insights. The course curriculum is designed to help you understand the role of statistics in fields including business, public policy, public health, and artificial intelligence.You will cover topics such as data visualization, algorithms, bioinformatics, data ethics, machine learning, and learn about various careers within data science and statistics, including data engineering, epidemiology, and sports analytics.
14. 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
Data in Action is a summer program for high school students who are interested in learning about data in the context of sustainability, journalism, and the environment. During the program, you will work with environmental data sets, learn how to analyze them to gather insights, and delve into data storytelling. You will work on your own data journalism piece on a topic that you're passionate about, sharpening skills in data interpretation, visualization, and storytelling. The program incorporates emotional engagement through activities such as mentorship, guest speakers, and collaborative projects.
15. 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 data science academy offers weekly classes where you will explore key data science concepts through interactive lectures and presentations. The course curriculum covers topics including data analysis, statistical methods, machine learning, and data visualization. You’ll practice what you learn through project-based activities, where you'll work with real-world data sets and case studies, giving you the chance to develop problem-solving skills. The program includes guest lectures by data science professionals who will share their experience and insights while providing an overview of opportunities in the field. The program culminates in a session where you will get to showcase your projects and findings to an audience.