Chapter 7.4 - Data Visualization Project
Time Estimate: 90 minutes
7.4.1. Introduction and Goals
In this lesson, you will work with a partner to identify and analyze a large data set that interests both of you. This project requires developing several questions, or hypotheses, about the data and then investigating them by creating visualizations to answer those questions. As you complete your project, keep track of your process on your portfolio using the reflection questions as a guide.
Learning Objectives: I will learn to
develop hypotheses about data
create a visualization from data
work with a partner to gain new insights about data
Language Objectives: I will be able to
summarize a set of data and describe what information can be extracted from it
use target vocabulary while making hypotheses, creating visualizations, and gaining knowledge from data, with the support of concept definitions from this lesson
7.4.2. Learning Activities
Process
Work collaboratively to research, investigate and analyze a large data set making sure that your project meets the following specifications.
Data Sources: For this project, your large data set must contain at least 1,000 data values or cells. (You may use one of these data sources, but you are encouraged to find others!)
Questions & Hypotheses: Brainstorm with your partner 3-5 questions and corresponding hypotheses that you believe can be answered using your chosen data set. First, write a question you have about the data set you chose. Now, convert that question into a hypothesis (a statement) with your prediction about the data. Hypotheses take the form of "If __________, then _________." For example, a hypothesis about student debt data could be, "If the tuition costs are higher at an institution, the student debt will be higher."
Download the data and put it into a Google Sheet. Record where you found the data set and when you downloaded it so you can cite it in your portfolio write-up.
Work collaboratively and use the tools available on the Google Spreadsheets and/or Google My Maps to determine if your 3-5 hypotheses are supported or refuted.
Create your own data visualizations that illustrate your hypotheses using Google Sheets and/or Google My Maps (do not use any existing visualizations that may have accompanied your data set, but create your own).
If you need a refresher on different types of graphs and when to use them, this short tutorial from MathGoodies may be helpful, as well as this reference to different types of charts available in Google Sheets.
For each chart, make sure it includes a title and has the appropriate values labeled on its axes.
Complete the portfolio reflection questions below.
(Optional) Give a 5-10 minute oral presentation with visuals (a PowerPoint with charts, graphs, etc.) Your presentations should follow the same structure as your portfolio write-up.
7.4.3. Summary
In this lesson, you learned how to:
Learning Objective CRD-1.C: Demonstrate effective interpersonal skills during collaboration.
Effective collaborative teams practice interpersonal skills, including but not limited to: communication, consensus building, conflict resolution, negotiation
Learning Objective DAT-2.A: Describe what information can be extracted from data.
Information is the collection of facts and patterns extracted from data.
Data provide opportunities for identifying trends, making connections, and addressing problems.
Digitally processed data may show correlation between variables. A correlation found in data does not necessarily indicate that a causal relationship exists. Additional research is needed to understand the exact nature of the relationship.
Learning Objective DAT-2.C: Identify the challenges associated with processing data.
Data sets pose challenges regardless of size, such as: the need to clean data, incomplete data, invalid data, and the need to combine data sources.
Cleaning data is a process that makes the data uniform without changing its meaning (e.g., replacing all equivalent abbreviations, spellings, and capitalizations with the same word).
Learning Objective DAT-2.D: Extract information from data using a program.
Tables, diagrams, text, and other visual tools can be used to communicate insight and knowledge gained from data.
Programs such as spreadsheets help efficiently organize and find trends in information.
Some processes that can be used to extract or modify information from data include the following: transforming every element of a data set, such as doubling every element in a list, or extracting the parent's email from every student record, filtering a data set, such as keeping only the positive numbers from a list, or keeping only students who signed up for band from a record of all the student, combining or comparing data in some way, such as adding up a list of numbers, or finding the student who has the highest GPA , and visualizing a data set through a chart, graph, or other visual representation.
Learning Objective DAT-2.E: Explain how programs can be used to gain insight and knowledge from data.
Programs are used in an iterative and interactive way when processing information to allow users to gain insight and knowledge about data.
Programmers can use programs to filter and clean digital data, thereby gaining insight and knowledge.
Combining data sources, clustering data, and classifying data are parts of the process of using programs to gain insight and knowledge from data.
Insight and knowledge can be obtained from translating and transforming digitally represented information.
Patterns can emerge when data are transformed using programs.
7.4.4. Reflection: For Your Portfolio
Answer the following portfolio reflection questions as directed by your instructor. Questions are also available in this Google Doc where you may use File > Make a Copy to make your own editable copy.
Which data set did you select and why did you choose it?
Summarize the data included, being specific about the types of data (text, sounds, transactions, etc.) included. Make sure you list the title and the website (URL) where you found the data.
List your 3-5 hypotheses and the data visualizations that you created for each. (Include the visualizations as images on your portfolio or provide a link to them shared with your instructor.)
Explain how collaborating with a partner helped you gain new insight or knowledge about the data.
Identify at least one security and/or privacy concern that is associated with the data in the data set you chose.
Portfolio Reflection Questions
Make a copy of this document in your Portfolio Assignments folder and answer these questions in the spaces below. Once complete, turn in this assignment according to the steps given by your teacher.
7.4 Data Visualization Project Curriculum Page
Answer the questions using the boxes below:
1. Which data set did you select and why did you choose it?
Answer
2. Summarize the data included, being specific about the types of data (text, sounds, transactions, etc.) included. Make sure you list the title and the website (URL) where you found the data.
Answer
2. List your 3-5 hypotheses and the data visualizations that you created for each. (Include the visualizations as images on your portfolio or provide a link to them shared with your instructor.)
Answer
Hypothesis 1:
<insert visualization>
Hypothesis 2:
<insert visualization>
Hypothesis 3:
<insert visualization>
Hypothesis 4:
<insert visualization>
Hypothesis 5:
<insert visualization>
3. Explain how collaborating with a partner helped you gain new insight or knowledge about the data.
Answer
4. Identify at least one security and/or privacy concern that is associated with the data in the data set you chose.
Answer
Last updated