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APIntermediate
AP Statistics
Interpret data, probability, and inference with a practical AP Statistics framework.
📚 9 units🤖 AI-guided support✅ Practice questions included
Course Units
2025–26 College Board CED1
Exploring One-Variable Data15–23% of exam
1.1
Classifying Variables and Study Design
Coming Soon
1.2
Displaying Data — Graphs and Their Interpretation
Coming Soon
1.3
Measures of Center — Mean vs. Median
Coming Soon
1.4
Measures of Spread — Standard Deviation and IQR
Coming Soon
1.5
Normal Distribution and the Empirical Rule
Coming Soon
1.6
z-Scores, Percentiles, and Normal Probability
Coming Soon
1.7
Boxplots and Five-Number Summary
Coming Soon
1.8
Density Curves and the Area-as-Probability Convention
Coming Soon
2
Exploring Two-Variable Data5–7% of exam
2.1
Scatterplots and Correlation
Coming Soon
2.2
Least-Squares Regression Line — Interpretation
Coming Soon
2.3
Residuals and Assessing Linearity
Coming Soon
2.4
R² — Coefficient of Determination
Coming Soon
2.5
Influential Points and Leverage
Coming Soon
2.6
Transformations to Achieve Linearity
Coming Soon
2.7
Two-Way Tables and Association in Categorical Data
Coming Soon
2.8
Causation, Correlation, and Confounding
Coming Soon
3
Collecting Data12–15% of exam
3.1
Sampling Methods — Which to Use and Why
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3.2
Sampling Bias and Its Sources
Coming Soon
3.3
Experimental Design — The Three Principles
Coming Soon
3.4
Blocking in Experiments
Coming Soon
3.5
Causation in Experiments
Coming Soon
3.6
Ethics in Data Collection
Coming Soon
3.7
Simulation in Statistics
Coming Soon
3.8
Survey Design and Question Wording
Coming Soon
4
Probability, Random Variables, and Probability Distributions10–20% of exam
4.1
Probability Rules — Addition and Multiplication
Coming Soon
4.2
Conditional Probability and Independence
Coming Soon
4.3
Discrete Random Variables — Expected Value and Variance
Coming Soon
4.4
Binomial Distribution
Coming Soon
4.5
Geometric Distribution
Coming Soon
4.6
Continuous Probability Distributions
Coming Soon
4.7
Normal Distribution Calculations
Coming Soon
4.8
Law of Large Numbers and Simulation
Coming Soon
5
Sampling Distributions7–12% of exam
5.1
Sampling Distribution of p̂
Coming Soon
5.2
Sampling Distribution of x̄
Coming Soon
5.3
Central Limit Theorem — The Key Insight
Coming Soon
5.4
Sampling Distributions for Differences
Coming Soon
5.5
Bias and Variability of Estimators
Coming Soon
5.6
Effect of Sample Size on Sampling Distributions
Coming Soon
5.7
t-Distribution vs. z-Distribution
Coming Soon
5.8
Conditions for Inference — The Three Checks
Coming Soon
6
Inference for Categorical Data: Proportions12–15% of exam
6.1
Confidence Intervals for One Proportion
Coming Soon
6.2
Significance Tests for One Proportion
Coming Soon
6.3
Two-Sample Proportion Tests and Intervals
Coming Soon
6.4
Type I and Type II Errors and Power
Coming Soon
6.5
P-value Interpretation — The Most Tested Concept
Coming Soon
6.6
Confidence Interval as a Range of Plausible Values
Coming Soon
6.7
Conditions for Proportion Inference
Coming Soon
6.8
Selecting the Right Test — One vs. Two Sample
Coming Soon
7
Inference for Quantitative Data: Means10–18% of exam
7.1
One-Sample t-Test and t-Interval
Coming Soon
7.2
Two-Sample t-Procedures
Coming Soon
7.3
Matched Pairs t-Procedures
Coming Soon
7.4
Checking Conditions for Means Inference
Coming Soon
7.5
Interpreting Confidence Intervals for Means
Coming Soon
7.6
Statistical Significance vs. Practical Significance
Coming Soon
7.7
Errors in t-Procedures and Robustness
Coming Soon
7.8
Designing Studies for Specific Inference Goals
Coming Soon
8
Inference for Categorical Data: Chi-Square2–5% of exam
9
Inference for Quantitative Data: Slopes2–5% of exam