What is an AP Statistics Course

The AP Statistics course teaches students the fundamental ideas and techniques for gathering, analysing, and interpreting statistics. Exploring data, sampling and experimentation, probability and simulation, and statistical inference are four themes that run across the AP Statistics online course’s content, skills, and evaluation. Students develop conceptual knowledge via the use of technology, investigations, problem solving, and writing.

Prerequisites

Any secondary school student who has finished a second-year algebra course and has adequate mathematical competence and quantitative reasoning skills should consider taking the AP Statistics course. Because AP Statistics requires second-year algebra, it is generally taken in either the junior or senior year. The following factors influence whether or not a student should take AP Statistics and when they should take it:

• Students who want to take a science course in their senior year would substantially benefit by taking AP Statistics in their junior year.
• AP Statistics permits students who would not otherwise study mathematics in their final year to continue to enhance their quantitative skills.
• Precalculus should be included in a student’s high school programme, and AP Statistics should be taken concurrently with precalculus if they want to study calculus in college.
• In high school, students with the necessary mathematical experience are encouraged to take both AP Statistics and AP Calculus.

Course Content

Unit 1: Exploring One-Variable Data

You’ll learn how statisticians think about variation and how to represent data, describe data distributions, and make inferences based on a theoretical distribution.

Unit 2: Exploring Two-Variable Data

By expressing two-variable data, comparing distributions, characterising connections between variables, and utilising models to generate predictions, you’ll be able to expand on what you’ve learned thus far.

Unit 3: Collecting Data

You’ll learn about research design and the significance of randomization. You’ll learn how to deduce suitable inferences and generalisations from the findings of well-designed research.

Unit 4: Probability, Random Variables, and Probability Distributions

The principles of probability will be covered, as well as the probability distributions that serve as the foundation for statistical inference.

Unit 5: Sampling Distributions

You’ll set the groundwork for estimating population features and measuring confidence as you get a better knowledge of sample distributions.

Unit 6: Inference for Categorical Data: Proportions

You’ll study inference techniques for proportions of a categorical variable, laying the groundwork for a solid grasp of statistical inference, which you’ll revisit throughout the course.

Unit 7: Inference for Quantitative Data: Means

You’ll learn to examine quantitative data to draw conclusions about population means, building on the inference skills you gained in Unit 6.

Unit 8: Inference for Categorical Data: Chi-Square

Chi-square tests, which may be employed when there are two or more categorical variables, will be covered.

Unit 9: Inference for Quantitative Data: Slopes

You’ll learn how to create confidence intervals and perform significance tests for the slope of a regression model, which is not always the real slope but is based on a single sample from a sampling distribution.

Exam Pattern

Section 1: Multiple Choice

This portion will consist of 40 questions and will last 1 hour and 30 minutes, accounting for 50 percent of the overall score. The multiple-choice section assesses:

• Your comprehension of all 9 study units’ material
• Your ability to use all four of the course skills

Individual questions or sets of questions based on a common prompt are included in this section.

Section 2: Free Response

You’ll write responses to six questions in the free-response portion, including one investigation activity. This part will assess your ability to provide explanations or reasons utilising facts, definitions, or statistical inference as proof.

Part A:

• 1 multipart question with the primary goal of data collection
• 1 multipart inquiry with the primary goal of data exploration
• 1 multipart question with a primary goal on probability and sample distributions
• 1 question that focuses mostly on inference
• 1 question that incorporates at least two skill categories

1 investigative activity that examines many skill categories and topic areas and requires you to use your statistical knowledge in unexpected situations or in unusual ways.

Part B:

1 investigative work that examines many skill categories and topic areas and requires you to apply your statistical talents in novel situations.

Our Offerings

• 40+ hours of Live Classes with experienced faculty
• 40+ hours of assignment
• Unit wise test to access the understanding
• 6+ Full length mock tests
• Doubt clarification sessions
• Online self paced course for additional practice

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