Master AP Statistics: Grasp Concepts, Master Calculations, and Ace Exams
Master AP Statistics is an exam-focused course by Jeremy Gu, a Silicon Valley data expert and professor with advanced degrees in Statistics. Real-world examples with data and statistical methods make concepts easy to grasp.
What's included
8 live meetings
12 in-class hoursHomework
4+ hours per week. Each week, students will receive a homework assignment designed to reinforce the core concepts covered in class, ensuring a solid understanding of key topics. With 6-7 assignments throughout the course, each set is crafted to be completed within 45 minutes, focusing on basic concept questions, thought-provoking problems, and short practice exercises. These tasks encourage critical thinking and real-world application of statistical methods, helping students build confidence and proficiency. Homework will be reviewed at the start of each session, allowing for clarification and reinforcing understanding before moving on to new topics.Certificate of Completion
1 after class completionClass Experience
US Grade 9 - 12
Beginner - Intermediate Level
AP Statistics Foundations is an intensive, exam-focused course designed by Jeremy Gu, a seasoned data expert and professor with advanced degrees in Statistics. This course emphasizes understanding key statistical concepts, mastering calculations, and building confidence for the AP Statistics exam. By using real-world examples, interactive learning, and plenty of practice problems, this course ensures that even students with no prior background in statistics can excel. Course Format - Duration: 8 weeks, 1 class per week - Class Length: 90 minutes per session - Class Type: Live online, interactive sessions - Expected 6-8 hours per week of study Teaching Style The teaching style is interactive and engaging, focusing on simplifying complex concepts using: - Slides: Visually appealing presentations to illustrate core concepts - Real-World Examples: Practical scenarios to show how statistics applies to everyday situations and professional fields - Practice Problems: A variety of exercises categorized into 3 types: basic, integrated, and advanced problems to gradually build confidence and proficiency - Interactive Q&A Sessions: Encouraging students to ask questions and clarify doubts in real time, fostering an active learning environment Class Interactions - Live Problem-Solving: Students will participate in solving problems together during the sessions, guided by step-by-step explanations - Group Discussions: Opportunities to discuss concepts and applications in small groups, encouraging peer learning - Practice Exams: Mock exams at the end of the course to simulate the actual AP Statistics exam and provide performance feedback Why Choose This Course? - Expert Instruction: Taught by Jeremy Gu, who combines practical industry knowledge with extensive teaching experience - High-Impact Learning: Structured to cover essential AP Statistics topics quickly and effectively, with a focus on achieving the highest scores - Real-World Relevance: Learn how statistical methods form the backbone of data science and AI, giving insights into future career applications
Learning Goals
Rapidly cover all major AP Statistics topics in alignment with the AP Statistics Exam GuidelinesBuild strong foundational skills in key statistical concepts like data types, probability, and inference
Syllabus
Curriculum
Follows College Board Advanced Placement CurriculumStandards
Aligned with Advanced Placement (AP) Standards8 Lessons
over 8 WeeksLesson 1:
Introduction to AP Statistics & Exam Overview
• Overview of AP Statistics: Key topics and concepts covered in the course
• Understanding the AP Exam structure: multiple-choice vs. free-response questions
• How to prepare for the exam: study tips and creating a personalized study plan
• Introduction to statistical thinking and basic terminology 90 mins online live lesson
Lesson 2:
Exploring Data - Descriptive Statistics
• Types of data: Categorical vs. numerical, discrete vs. continuous
• Measures of central tendency: Mean, median, mode
• Measures of spread: Range, interquartile range, variance, standard deviation
• Graphical representations: Histograms, box plots, scatterplots, and bar charts 90 mins online live lesson
Lesson 3:
Exploring Data - Bivariate Data & Regression
• Relationships between variables: Correlation and causation
• Scatterplots and interpreting patterns
• Introduction to linear regression: Least-squares method, line of best fit
• Analyzing residuals and assessing model fit 90 mins online live lesson
Lesson 4:
Collecting Data - Sampling & Experimentation
• Sampling methods: Random, stratified, cluster, and systematic sampling
• Designing surveys and experiments: Reducing bias and errors
• Understanding observational studies vs. controlled experiments
• Key concepts: Randomization, replication, control, and blocking 90 mins online live lesson
Other Details
Pre-Requisites
No prior statistics knowledge is required, but a basic understanding of algebra and mathematical concepts will be helpful. Students should be comfortable with using a calculator, interpreting graphs, and performing simple calculations.
External Resources
Learners will not need to use any apps or websites beyond the standard Outschool tools.
Sources
AP Statistics Course Description
AP Statistics Official Practice Guide
AP classroom
https://account.collegeboard.org/login/login?DURL=https://apclassroom.collegeboard.org/
Joined December, 2023
Teacher expertise and credentials
3 Degrees
Master's Degree in Science from University of Washington
Bachelor's Degree in Mathematics from University of Minnesota
Bachelor's Degree in Science from University of Minnesota
I have 11 years of teaching experience in various subjects related to data science, analytics, and statistics, as well as experience guiding students through strategic decision-making processes. My teaching background includes but not limit to:
- Data Streaming (MSDS 682) - Fall 2023, University of San Francisco Format: In-Person, Graduate level Role: Lead/Primary Instructor Class size: 9 students
- Connecting Data Analytics with Managerial Success (BUS 36) - Summer 2024, Stanford Continuing Studies Format: In-Person, Extension Studies Role: Lead/Primary Instructor Class size: 25 students
- Non-parametric Modeling (STAT 527) - Spring 2014, University of Washington Format: In-Person, Graduate level Role: Teaching Assistant Class size: 50 students
- Categorical Data Analysis (STAT 536) - Spring 2013, University of Washington Format: In-Person, Graduate level Role: Teaching Assistant Class size: 50 students
Reviews
Live Group Course
$25
weekly or $199 for 8 classes1x per week, 8 weeks
90 min
Live video meetings
Ages: 14-18
6-12 learners per class
