Chapter 2: Displaying and Summarizing Categorical Data

• Conditional distributions focus on a specific category within another variable.
• Comparing conditional distributions helps us identify associations between variables.
• If percentages vary significantly between groups, an association exists.

Each section follows the same learning progression: understand the concept, practice the skill, think like a statistician, then apply your learning to authentic data.

Whether learning independently or teaching a class, the learning path below is designed to help students master the concepts in this section. Page references below correspond to the Real World Statistics instructional system.

Step 1: Watch the lesson video

Watch the lesson video and take notes on the key ideas.

Step 2: Read the section

Read pages 52-55 to reinforce the concepts introduced in the lesson.

Step 3: Practice what you've learned

Complete the 3 multi-part practice questions on pages 55-56. Check your work using the Answer Key, then review and correct any questions you missed before moving on.

Step 4: Think like a statistician
Explore Enrichment: Role-Based Statistical Analysis Tasks and the Chapter Dataset to apply statistical thinking in real-world contexts.

If you'd like additional guidance while working through the practice questions, explore the Worked Solutions Manual for step-by-step solutions and explanations.

Examples of authentic statistical work supported by this section include:

• interpreting contingency tables using marginal and conditional distributions to compare groups and identify possible associations (e.g., library membership and reading frequency from a community survey, or participation in tutoring and course completion from a district report) 
• writing evidence-based reports that explain whether two categorical variables appear to be associated using percentages from contingency tables (e.g., disaster preparedness by region from an emergency management survey, or employee training participation by certification status from a workplace audit) 
• comparing conditional percentages across groups to support recommendations or policy decisions (e.g., recycling participation by housing type from a municipal study, or voter turnout by age group from an election analysis) 

You may use these ideas to design your own investigations or explore the Real World Statistics System.

Enrichment: Role-Based Statistical Analysis Tasks place students in the role of a statistician working on real research problems, where they evaluate data, justify decisions, and communicate findings clearly. Each section includes multiple enrichment tasks, including one with a model response that demonstrates statistical reasoning in context, showing how evidence is evaluated, decisions are justified, and conclusions are communicated. This serves as a bridge to working with authentic datasets and independent statistical investigation within each chapter.

Available in the Interactive eBook at the end of the section (page 56) and in the Appendix of the Print Book (page 401).

Teaching with Real World Statistics: These structured learning paths—including Enrichment tasks and Chapter Datasets—can be adapted or copied directly into Canvas, Google Classroom, Schoology, and other learning management systems to simplify lesson planning and student assignments.