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Elevate AP Journey: With Anannt Education
Course Structure π
- 40+ Hours of Learning π: Interactive sessions, in-person & online.
- Small Batches π₯: Max 10 students for personalized focus.
- Custom Plans π―: Diagnostic tests tailor your study journey.
- Regular Assessments βοΈ: Advanced testing portal for constant improvement.
Study Material π
- Expert Tutors π©βπ«: Personalized guidance from seasoned pros.
- Rich Resources π: Detailed notes, video tutorials, and topic-wise tests.
- Mock Tests π: 5 full-length exams for a real test experience.
- Online Portal π»: Quizzes and explanations for deeper learning.
Anannt Advantage β¨
- Dedicated Mentors π: Celebrated for exceptional mentorship.
- Holistic Approach π: Blends guidance, support, and materials for success.
- Proven Methods π: Achieve excellence with our tested teaching strategies.
- Unlock Potential π: Realize your ambitions and excel in AP Statistics.
AP Statistics Syllabus
Unit 1: Exploring One-Variable Data (15%β23%)
- π Variation in variables: Understand categorical vs. quantitative, measure center and spread.
- π Data representation: Master histograms, box plots, stem-and-leaf, and bar charts.
- π’ Statistics: Mean, median, mode, range, standard deviation, z-scores, percentiles.
- π Distributions: Describe skewness, modality, outliers; compare using plots.
Unit 2: Exploring Two-Variable Data (5%β7%)
- π² Categorical comparisons: Two-way tables, segmented bar charts.
- π Bivariate data: Scatter plots, correlation, linear regression, residuals.
Unit 3: Collecting Data (12%β15%)
- π Study design: Research questions, Basics of Designing a study.
- Sampling Methods: Simple Random Sampling, Stratified sampling, and cluster sampling and Bias.
- π§ͺ Experiment design: Treatments, subject selection, randomization.
Unit 4: Probability & Distributions (10%β20%)
- π² Simulations:Β Basics of simulation, including Monte Carlo simulation, Random variables.
- Probability of Random Event: Calculate probabilities of simple, compound events and conditional probability.
- Binnomial Distribution & Geometric Distribution: Properties, including calculating probabilities and expected values.
Unit 5: Sampling Distributions (7%β12%)
- π Variation in Statistics: In-depth analysis of sample means and proportions distributions.
- π Central Limit Theorem: Significance and practical applications.
Unit 6: Inference for Categorical Data (12%β15%)
- π Constructing and interpreting a confidence: Detailed study on constructing and interpreting confidence intervals for proportions using sample proportion and Standard error.
- π― Introduction to Chi-square tests for association in categorical data.
Unit 7: Inference for Quantitative Data (10%β18%)
- π Techniques for comparing means, including t-tests and ANOVA.
- π Understanding assumptions and conditions for inferential tests.
Unit 8: Chi-Square Tests (2%β5%)
- π Mastery of chi-square goodness of fit tests, including assumptions and conditions.
- π‘ Exploring chi-square tests for homogeneity and independence with real-world examples.
Unit 9: Inference for Slopes (2%β5%)
- π Advanced understanding of regression inference, including conditions for the regression inference.
- π― Focus on interpreting and constructing confidence intervals and hypothesis tests for the slope of a regression line.
π AP Statistics Exam Structure π
Section 1: Multiple Choice
- π’ Number of Questions: 40
- β° Time Allotted: 1 hour and 30 minutes
- π Content Coverage: Questions span across all units, testing understanding, application, and integration of course content.
- π‘ Question Types: Both individual and sets of questions based on scenarios.
- β Scoring: Correct answers contribute towards the total score, with no penalty for incorrect answers.
Section 2: Free Response
- π’ Number of Questions: 6 (including 1 investigative task)
- β°Time Allotted: 1 hour and 30 minutes
- π Content Coverage: Emphasizes data analysis, experimental design, probability, and inference, reflecting the course’s focus on investigation and exploration.
- π‘ Question Types: Questions demand thorough responses that involve explaining statistical concepts, interpreting results, and justifying answers.
- π Investigative Task: Represents a more complex analysis scenario requiring integration of multiple content areas.