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Ch 8: Cambridge Pre-U Math Short Course: Correlation & Regression

About This Chapter

Correlation and regression are two methods of analysis used to study variables among data. This chapter of the Cambridge Pre-U Math Short Course review goes over these methods to get you ready for the exam.

Cambridge Pre-U Math Short Course: Correlation & Regression - Chapter Summary

Utilizing correlation and regression in your research of statistics is a multi-layered process that can present obstacles, but this chapter of video lessons in the Cambridge Pre-U Math Short Course curriculum is designed to guide you through any trouble you are having while reviewing for your final exam. The topics contained in this chapter include the following:

  • Uses of bivariate data
  • Creating and interpreting scatterplots
  • The formula for simple linear regression
  • Process of analyzing residuals
  • Slopes and intercepts of linear models
  • The correlation coefficient
  • Differences in correlation and causation
  • Interpreting linear relationships

The included set of self-assessment quizzes gives you a chance to test yourself on your knowledge of correlation and regression without any of the pressure of the actual Cambridge Pre-U exam, and also gives you an idea of what to expect when the day of your exam arrives. If you have extra questions about the content of this course, you can immediately contact one of the experts via the dashboard.

Cambridge Pre-U Math Short Course: Correlation & Regression Chapter Objectives

The Cambridge Pre-U Math Short Course final exam is a traditional final exam given at the end of this university-level class. Questions about correlation and regression will be included in the 'Statistics, section of the exam. Also known as Paper 2, this section has 80 questions and makes up 55% of the score. You'll have two hours to complete this section.

10 Lessons in Chapter 8: Cambridge Pre-U Math Short Course: Correlation & Regression
Test your knowledge with a 30-question chapter practice test
What is Bivariate Data? - Definition & Examples

1. What is Bivariate Data? - Definition & Examples

In this lesson, you will be learning about the definition and uses of bivariate data. We will also compare and contrast the characteristics of univariate data and bivariate data.

Creating & Interpreting Scatterplots: Process & Examples

2. Creating & Interpreting Scatterplots: Process & Examples

Scatterplots are a great visual representation of two sets of data. In this lesson, you will learn how to interpret bivariate data to create scatterplots and understand the relationship between the two variables.

Simple Linear Regression: Definition, Formula & Examples

3. Simple Linear Regression: Definition, Formula & Examples

Simple linear regression is a great way to make observations and interpret data. In this lesson, you will learn to find the regression line of a set of data using a ruler and a graphing calculator.

Problem Solving Using Linear Regression: Steps & Examples

4. Problem Solving Using Linear Regression: Steps & Examples

Linear regression can be a powerful tool for predicting and interpreting information. Learn to use two common formulas for linear regression in this lesson.

Analyzing Residuals: Process & Examples

5. Analyzing Residuals: Process & Examples

Can you tell what's normal or independent and what's not? Sometimes, we need to figure this out in the world of statistics. This lesson shows you how as it explains residuals and regression assumptions in the context of linear regression analysis.

Interpreting the Slope & Intercept of a Linear Model

6. Interpreting the Slope & Intercept of a Linear Model

You've probably seen slope and intercept in algebra. These concepts can also be used to predict and understand information in statistics. Take a look at this lesson!

Spearman's Rank Correlation Coefficient

7. Spearman's Rank Correlation Coefficient

Spearman's Rank Correlation provides a unique method for measuring the correlation of paired data points. This lesson shows how this value is derived, and explores how this differs from a basic correlation computation.

The Correlation Coefficient: Definition, Formula & Example

8. The Correlation Coefficient: Definition, Formula & Example

The correlation coefficient is an equation that is used to determine the strength of the relationship between two variables. This lesson helps you understand it by breaking the equation down.

Correlation vs. Causation: Differences & Definition

9. Correlation vs. Causation: Differences & Definition

When conducting experiments and analyzing data, many people often confuse the concepts of correlation and causation. In this lesson, you will learn the differences between the two and how to identify one over the other.

Interpreting Linear Relationships Using Data: Practice Problems

10. Interpreting Linear Relationships Using Data: Practice Problems

Understanding linear relationships is an important part of understanding statistics. This lesson will help you review linear relationships and will go through three practice problems to help you retain your knowledge. When you are finished, test out your knowledge with a short quiz!

Chapter Practice Exam
Test your knowledge of this chapter with a 30 question practice chapter exam.
Not Taken
Practice Final Exam
Test your knowledge of the entire course with a 50 question practice final exam.
Not Taken

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