# Unit 2, Section 3: What Are the Chances That You Are Stressing or Chilling?

Instructional Days: 8

## Enduring Understandings

Permutations of data provide a model that shows us how the world behaves if chance is the only reason for differences between groups or for associations between variables. If our actual observation is a rare permutation, this suggests that chance is not a good explanation for the difference or association. On the other hand, if the actual observation is a common permutation, this suggests that chance may be a valid explanation. Differences between permuted data and actual data suggest that the chance model can be rejected and there is a dependent relationship between two variables.

## Engagement

Students will read the Huffington Post article titled Don’t Take My Stress Away to set the stage for the Stress/Chill Campaign. High school students who expected, and wanted, to feel stressed out by school wrote this article. The article is found at:
http://www.huffingtonpost.com/jack-cahn/dont-take-my-stress-away_b_2090203.html

## Learning Objectives

Statistical/Mathematical:

S-IC 2: Decide if a specified model is consistent with results from a given data-generating process, e.g., using simulation.

S-IC 6: Evaluate reports based on data.

Data Science:

Understand that a chance model serves as an indicator of whether or not associations in the actual data are due to chance (understand why a plot might appear to have a trend, but may actually be the result of randomness). Understand that simulations provide a way of comparing expected chance outcomes to real outcomes in order to determine if a model and actual data appear consistent. Learn about merging data sets by understanding the structure of both data sets and the logic of the way they will be combined.

Applied Computational Thinking using RStudio:

• Permutations of data, determining if actual data is similar to permuted data

• Merge multiple data sets together based on a common variable

• Create permutations using a merged data set

Real-World Connections:

In media, citizens read about results and scientific studies in which treatments are applied. In real life, one can ask the question: Does this happen by chance? Understanding chance helps us interpret media reports of scientific and medical findings.

## 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. Stress/Chill Participatory Sensing Campaign: Students will monitor how they feel at different times of the day – whether they are “stressing” or “chilling.” Along with how they feel, they will make observations regarding other factors, such as being alone or with others, what they are doing at that moment, and why they are doing that activity.

Data Files:

1. Students’ Personality Color survey data (colors)

2. Students’ Stress/Chill campaign data

3. Titanic data set (titanic.rda)

4. Horror Movie data set (slasher.rda)