Unit3, Section2: Would You Look at That?

Instructional Days: 4

Enduring Understandings

An observational study is a data collection method in which subjects are observed and outcomes are recorded. Unlike experiments, it may not be possible to assign subjects to treatment and control groups in observational studies, which impedes our ability to control for confounding factors. This means that researchers must rely on existing control and treatment groups to observe the outcomes. Observational studies can show associations in the data, but cause and effect relationships can only be concluded with experiments.


Students will participate in the Observational Studies Activity described in Lesson 5. They will record information that can be obtained through pictures. The data will then be analyzed to see if there are any variables related to the number of friends a person has on social media.

Learning Objectives


S-IC 1. Understand statistics as a process for making inferences about population parameters based on a random sample from that population.

S-IC 3. Recognize the purposes of and differences among sample surveys, experiments, and observational studies; explain how randomization relates to each.

S-IC 6: Evaluate reports based on data.

Data Science:

Understand that data from observational studies can help us find associations among variables. Explain why some variables that are not related in reality might look as though they are due to the presence of confounding factors.

Applied Computational Thinking using RStudio:

• Download data from the Internet that was collected via an observational study.

• Clean data set by adding variable names.

• Create scatterplots of two variables and determine possible relationships between them, as well as identify potential confounding variables.

Real-World Connections:

Economists, psychologists, and biologists conduct observational studies to study human behavior. For example, observational studies are used in epidemiology to study outbreaks of illnesses and people’s behavioral patterns.

Language Objectives

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

  1. Students will record information about a set of high school students by observing characteristics given in a picture.

Data File:

  1. Lung Capacity of Children data set found at

Legend for Activity Icons