Advanced Placement Statistics is equivalent to a one-semester, introductory, non-calculus-based college statistics course. The rigor of this course is consistent with colleges and universities and will prepare students for the Advanced Placement exam in May. Upon successful completion of the exam, students may receive college credit and will be well-prepared for advanced statistics coursework. Additional details on each course from the College Board can be found here: AP Statistics.
In this course, students will explore three big ideas:
(1) 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. 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.
(2) Patterns 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.
(3) 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.
This course incorporates a variety of textbook and multimedia resources including an adaptive problem set platform that provides various feedback on student assessments. Students will also connect concepts in statistics to real-world applications, in order to develop a deeper understanding of statistics in today’s world.
Students will be expected to enroll in My AP Classroom through their VHS Learning AP course and will be guided to complete review work in My AP Classroom throughout the course. My AP Classroom resources include AP Daily Videos and unit-based Personal Progress Checks, which include AP-style multiple choice and free response questions.
Students enrolled in VHS Learning Advanced Placement courses with a passing grade are expected to take the AP Exam. Students register for AP exams through their local school or testing site as “Exam Only” students. AP exam scores will be reported to VHS Learning through My AP Classroom; exam results will not affect the student’s VHS Learning grade or future enrollment in VHS Learning courses.
About the Self-Paced Course Model
Self-Paced courses are comprehensive, self-paced courses designed for students who need or desire more flexibility in their academic schedule. VHS Learning teachers will regularly interact with students in asynchronous discussions, will host weekly office hours, and will invite students to monthly 1-on-1 progress meetings. Teachers will support students, answer questions, and provide feedback on work. Students will work independently on course activities; the course does not include class discussion assignments or other collaborative work.
Students may start this course on any Wednesday from September through the first Monday in December. Students must maintain enrollment for a minimum of 20 weeks and have until mid-June to complete all assignments in the course. It is expected that students will work for approximately 330 hours to complete this course, though the amount of time may vary depending on a student’s work habits and comfort with the material.
Course Essential Questions:
- How can we determine whether differences between measures represent random variation or meaningful distinctions?
- How can we use simulations to anticipate patterns in data?
- How can we analyze data to identify relationships between variables in order to make appropriate and logical conclusions or decisions?
Course Learning Objectives:
- Select methods for collecting and/or analyzing data for statistical inference.
- Describe patterns, trends, associations, and relationships in data.
- Explore random phenomena.
- Develop an explanation or justify a conclusion using evidence from data, definitions, or statistical inference.