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Unit 1, Section 3: Would You Look at the Time!

Instructional Days: 9

Enduring Understandings

Data are useful for evaluating claims and reports. Summaries of categorical and numerical data show important features and patterns in the data. Data summaries provide evidence to make claims.


The Bureau of Labor Statistics (BLS) collects data about daily time-use of Americans. Students will explore an interactive graphic titled How Men and Women Spend Their Days created by Nathan Yau, that uses data from the American Time Use Survey, to spark their curiosity about how they spend their own time. This graphic can be found at:

Learning Objectives


S-ID 5: Summarize categorical data for two categories in two-way frequency tables. Interpret relative frequencies in the context of data (including joint, marginal, and conditional relative frequencies). Recognize possible associations and trends in the data.

S-IC 6: Evaluate reports based on data.

Data Science:

Understand that data are collected and stored in particular formats. Before data can be analyzed, it must be cleaned so it can be read.

Applied Computational Thinking Using RStudio:

• Create tabular displays of categorical data and summaries of numerical data.

• Create two-way frequency (and relative frequency) tables.

• Use RStudio to calculate joint, marginal, and conditional relative frequencies.

• Subset data frames and create new categorical variables from numerical variables.

• Clean and polish data to make it readable.

Real-World Connections:

Make claims that are based on data and begin to evaluate reports that make claims based on data.

Language Objectives

  1. Students will use complex sentences to construct summary statements about their understanding of data, how it is collected, how it is used, and how to work with it.

  2. Students will engage in partner and whole group discussions and presentations to express their understanding of data science concepts.

  3. Students will use complex sentences to write informative short reports that use data science concepts and skills.

  4. Students will read informative texts to evaluate claims based on data.

Data File or Data Collection Method

Data Collection Method:

Time-Use Participatory Campaign: Students will monitor the amount of time they devote to activities such as sleeping, studying, eating, and partaking in media.

Data Files:

  1. Students’ Time-Use campaign data

  2. American Time-Use Survey (ATUS) data

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