(1:15pm EST) Intro to Probability
SAT Score Range
•
7 sessions
•
TD
NY
AS
+12
•
🔥 5 spots left!
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About
About
A little bit about me! I just graduated high school and I'm excited to offer this short course in statistics. I scored a 5 on the AP Statistics exam last year and I also have experience in Discrete Mathematics.
This summer course offers a mathematically rigorous yet accessible introduction to probability.
Students will explore:
- Basic probability and sample spaces
- Simulations and the Law of Large Numbers
- Compound and conditional probability
- Bayes' Theorem
- Discrete probability distributions, including binomial models
The course consists of six main sessions, each one hour long, having a clear, structured lecture followed by guided example problems. A seventh and final session will offer a comprehensive review and a set of cumulative problems to reinforce learning and retention. After each session, lecture notes as well as optional review materials will be provided to help students revisit key ideas at their own pace.
Ideal for students preparing for AP Statistics, Discrete Mathematics, or anyone curious about the subject of probability.
Tutored by
✋ ATTENDANCE POLICY
If you need to miss a session, no problem! Just let me know in advance or as soon as you’re able. Recordings, notes, and review materials will be provided so you can stay caught up at your own pace. My goal is to support your learning, so don’t hesitate to reach out if you need help catching up or reviewing content.
SESSION 5
1
Jul
SESSION 5
AP Statistics
AP Statistics
Tue 5:15 PM - 6:15 PM UTCJul 1, 5:15 PM - 6:15 PM UTC
Bayes’ Theorem, Inverse probabilities, and the Law of Total Probability
Present Bayes’ Theorem as a tool for computing inverse probabilities. Derive its formula using the Law of Total Probability and apply it to problems.
Topics covered:
- Bayes’ Theorem
- Inverse probabilities
- Law of Total Probability
SESSION 6
3
Jul
SESSION 6
AP Statistics
AP Statistics
Thu 5:15 PM - 6:15 PM UTCJul 3, 5:15 PM - 6:15 PM UTC
Overview of Probability Distributions
Define discrete probability distributions and conditions for validity. Construct and interpret uniform distributions. Introduce the concepts of expected value and standard deviation. Look at the binomial distribution and its parameters.
Topics covered:
- Discrete distributions
- Uniform distribution
- Expected value and Standard deviation
- Binomial distribution and Binomial formula
SESSION 7
8
Jul
SESSION 7
Review
Review
Tue 5:15 PM - 6:15 PM UTCJul 8, 5:15 PM - 6:15 PM UTC
Cumulative Review and Final Assessment
Review Topics:
- Compound probability
- Conditional reasoning
- Probability distributions