## Lesson Summary

Pre-Lesson Preparation: Students need to have already chosen a topic and had it approved by the instructor. Students can use the following sources to help choose a data set:

Summary:

This lesson is the summative assessment for Unit 4 on Data Analysis.    Students will select a data set and write a small Python program to analyze the data.  Students will then write a summary of their findings to demonstrate understanding of the data analysis process.

Outcomes:

• This unit assessment is designed to provide more practice in project based-work to prepare students for the final performance project at the end of this class.

Overview:

1. Getting Started (5 min): Overview of task for the day.
2. Independent Activity (40 min): Individually or in pairs, students collect and analyze data on their topic.
3. Wrap Up (5 min): Overview of homework goals and expectations.
4. Homework: Individual two-page summary about their findings.

## Math Common Core Practice:

• MP1: Make sense of problems and persevere in solving them.
• MP2: Reason abstractly and quantitatively.
• MP3: Construct viable arguments and critique the reasoning of others.
• MP4: Model with mathematics.
• MP5: Use appropriate tools strategically.
• MP6: Attend to precision.
• MP7: Look for and make use of structure.

## Common Core Math:

• S-ID.1-4: Summarize, represent, and interpret data on a single count or measurement variable
• S-ID.5-6: Summarize, represent, and interpret data on two categorical and quantitative variables
• S-ID.7-9: Interpret linear models
• S-IC.3-6: Make inferences and justify conclusions from sample surveys, experiments and observational studies

## Common Core ELA:

• RST 12.3 - Precisely follow a complex multistep procedure
• WHST 12.5 - Develop and strengthen writing as needed by planning, revising, editing, rewriting
• WHST 12.6 - Use technology, including the Internet, to produce, publish, and update writing products
• WHST 12.7 - Conduct short as well as more sustained research projects to answer a question

## NGSS Practices:

• 1. Asking questions (for science) and defining problems (for engineering)
• 2. Developing and using models
• 3. Planning and carrying out investigations
• 4. Analyzing and interpreting data
• 5. Using mathematics and computational thinking

## Key Concepts

Students will demonstrate their understanding of the process of collecting and evaluating data.

## Essential Questions

• How can computation be employed to help people process data and information to gain insight and knowledge?
• How can computation be employed to facilitate exploration and discovery when working with data?
• What opportunities do large data sets provide for solving problems and creating knowledge?
• How are algorithms implemented and executed on computers and computational devices?
• How are algorithms evaluated?

## Teacher Resources

Student computer usage for this lesson is: required

Rubric provided on Google Drive - Rubric - Unit 4 Summative Assessment.htm in the lesson folder.

# Getting Started (5 min)

Verify that every student has selected a topic (approved by the instructor in advance) and address what the goal is for today.

# Independent Activity (40 min)

Students will either individually or in pairs (instructor's decision) create a small program that reads data from a file, analyzes it, creates a simple simulation and finally writes data to a file.

# Wrap Up (5 min)

Presentation about the expectations of the homework assignments.

# Homework

Each student should create a 2-page typed summary that explains the following areas:

• The chosen data
• Why the data topic was chosen
• The analysis process
• The results of the analysis process
• The coding process used for data analysis

## Options for Differentiated Instruction

Instructor has the option to have students work individually or in pairs for this assessment.

## Formative Assessment

Review Rubric with class and clarify expectations.

## Summative Assessment

Students will be assigned a unit project, with a topic of their choice, to demonstrate their understanding and mastery of the concepts of data collection and analysis.