Displaying Quantitative Data
Students create and interpret dot plots, histograms, and box plots for quantitative data. They learn to describe the shape, center, and spread of distributions.
About This Topic
Students create and interpret dot plots, histograms, and box plots for quantitative data. They learn to describe the shape, center, and spread of distributions.
Key Questions
- Which graphical display is most appropriate for a given dataset?
- How do we describe the shape of a distribution?
- What constitutes an outlier?
Active Learning Ideas
See all activities→Activities & Teaching Strategies
See all activities
Planning templates for Statistics
5E Model
The 5E Model structures lessons through five phases (Engage, Explore, Explain, Elaborate, and Evaluate), guiding students from curiosity to deep understanding through inquiry-based learning.
Unit PlannerMath Unit
Plan a multi-week math unit with conceptual coherence: from building number sense and procedural fluency to applying skills in context and developing mathematical reasoning across a connected sequence of lessons.
RubricMath Rubric
Build a math rubric that assesses problem-solving, mathematical reasoning, and communication alongside procedural accuracy, giving students feedback on how they think, not just whether they got the right answer.
More in Exploring One-Variable Data
Categorical Data Analysis
Students summarize categorical data using frequency tables, bar charts, and pie charts. They analyze marginal and joint frequencies to identify potential associations.
8 methodologies
Summarizing Quantitative Data
Students calculate measures of center (mean, median) and spread (standard deviation, IQR). They evaluate how extreme values affect these numerical summaries.
8 methodologies
The Normal Distribution
Students model data distributions using the normal curve and apply the Empirical Rule. They calculate and interpret z-scores to compare values from different datasets.
8 methodologies