AP Statistics 12
AP Statistics Course Overview
Variation and Distribution
The distribution of measures for individuals within a sample or population describes variation. The value of a statistic varies from sample to sample. How can we determine whether differences between measures represent random variation or meaningful distinctions? Statistical methods based on probabilistic reasoning provide the basis for shared understandings about variation and about the likelihood that variation between and among measures, samples, and populations is random or meaningful.
Pattern and Uncertainty
Statistical tools allow us to represent and describe patterns in data and to classify departures from patterns. Simulation and probabilistic reasoning allow us to anticipate patterns in data and to determine the likelihood of errors in inference.
Data-Based Predictions, Decisions, and Conclusions
Data-based regression models describe relationships between variables and are a tool for making predictions for values of a response variable. Collecting data using random sampling or randomized experimental design means that findings may be generalized to the part of the population from which the selection was made. Statistical inference allows us to make data-based decisions.
AP Statistics is an introductory college-level statistics course that introduces students to the major concepts and tools for collecting, analyzing, and drawing conclusions from data. Students cultivate their understanding of statistics using technology, investigations, problem solving, and writing as they explore concepts like variation and distribution; patterns and uncertainty; and data-based predictions, decisions, and conclusions.
Where does this course fit?
- Pre-requisite: Pre-Calculus 11 recommended
- Graduation Status: Grade 12 elective for graduation
- An optional AP exam in May (requires exam fee) where a score of 4 or 5 may be used as university course credit.
- Graphing calculator is recommended
- Graphing calculator is required if you are writing the AP exam
Exploring One-Variable Data
We will learn to talk about data in real-world contexts. Variability in data may seem to suggest certain conclusions, but not all variation is meaningful. Statistics allows us to develop shared understandings of uncertainty and variation.
Exploring Two-Variable Data
We will explore relationships in two-variable categorical or quantitative data sets, and use graphical and numerical methods to investigate an association between two categorical variables.
In this unit, we will learn important principles of sampling and experimental design.
Probability, Random Variables, and Probability Distributions
Probabilistic reasoning allows statisticians to quantify the likelihood of random events over the long run and to make statistical inferences. Simulations and concrete examples can be used to understand the abstract definitions and calculations of probability.
This unit applies probabilistic reasoning to sampling, introducing sampling distributions of statistics that will be used for inferences.
Inference for Categorical Data: Proportions
This unit introduces statistical inference. We will analyze categorical data to make inferences about binomial population proportions, construct and interpret confidence intervals, and perform significance tests to evaluate claims about population proportions.
Inference for Quantitative Data: Means
We will analyze quantitative data to make inferences about population means. We will also learn how and why conditions for inference with proportions and means are similar and different.
Inference for Categorical Data: Chi-Square
We will make connections between frequency tables, conditional probability, and calculating expected counts. The chi-square statistic is introduced to measure the distance between observed and expected counts relative to expected counts.
Inference for Quantitative Data: Slopes
We will learn how to construct confidence intervals for and perform significance tests about the slope of a population regression line when appropriate conditions are met.
Assessment Percentage Breakdown
Percentage of the Course
You have up to a year to complete your course.