AP Statistics Practice Test
- Variation in categorical and quantitative variables (0)
- Representing data using tables or graphs (10)
- Calculating and interpreting statistics (10)
- Describing and comparing distributions of data (10)
- The normal distribution (10)
- Comparing representations of 2 categorical variables (10)
- Calculating statistics for 2 categorical variables (10)
- Representing bivariate quantitative data using scatter plots (10)
- Describing associations in bivariate data and interpreting correlation (10)
- Linear regression models (10)
- Residuals and residual plots (10)
- Departures from linearity (10)
- Planning a study (10)
- Sampling methods (10)
- Sources of bias in sampling methods (10)
- Designing an experiment (10)
- Interpreting the results of an experiment (10)
- Using simulation to estimate probabilities (0)
- Calculating the probability of a random event (10)
- Random variables and probability distributions (10)
- The binomial distribution (10)
- The geometric distribution (10)
- Variation in statistics for samples collected from the same population (0)
- The central limit theorem (10)
- Biased and unbiased point estimates (10)
- Sampling distributions for sample proportions (10)
- Sampling distributions for sample means (10)
- Constructing and interpreting a confidence interval for a population proportion (10)
- Setting up and carrying out a test for a population proportion (10)
- Interpreting a p-value and justifying a claim about a population proportion (10)
- Type I and Type II errors in significance testing (10)
- Confidence intervals and tests for the difference of 2 proportions (10)
- Constructing and interpreting a confidence interval for a population mean (10)
- Setting up and carrying out a test for a population mean (10)
- Interpreting a p-value and justifying a claim about a population mean (10)
- Confidence intervals and tests for the difference of 2 population means (10)
- The chi-square test for goodness of fit (10)
- The chi-square test for homogeneity (10)
- The chi-square test for independence (10)
- Selecting an appropriate inference procedure for categorical data (10)
- Confidence intervals for the slope of a regression model (10)
- Setting up and carrying out a test for the slope of a regression model (10)
- Selecting an appropriate inference procedure (10)
Exam Format & Components
Section 1 : Multiple Choice
40 Questions | 1hr 30mins | 50% of Score
The multiple-choice section evaluates your comprehensive knowledge and analytical skills in statistics. Key assessment areas include:
- Comprehensive Knowledge: Test understanding across all units of statistics, covering diverse topics from data collection to probability and inference.
- Skill Application: Determine how effectively you can apply analytical and interpretative skills to solve statistical problems.
- Question Format: Consists of individual and set-based questions, each centered around shared prompts or datasets that challenge your ability to analyze and interpret data.
Section 2 : Free Response
6 Questions | 1hr 30mins | 50% of Score
The free-response section is designed to assess your ability to articulate and justify statistical analyses and conclusions:
- Data Collection and Analysis: Focus on collecting and exploring data to uncover insights and inform decisions.
- Probability and Sampling: Address complex problems involving probability theories and sampling distributions.
- Inference: Draw and justify conclusions from data using statistical inference techniques.
- Synthesis of Concepts: Tackle comprehensive questions that require integrating multiple statistical concepts and techniques.
- Investigative Task: Engage in a capstone task that challenges you to apply your statistical knowledge creatively and innovatively to non-routine situations.
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