Learning Objectives/Outcomes:
Students will identify 4 data types and analyze the appropriateness of data visualizations for given data types.
Students will use Google Sheets to be able to utilize:
built-in functions to meaningfully analyze data including relative and absolute references;
filter, sort, and manipulate rows;
and prepare line charts, bar charts, scatter plots, and histograms.
Learning Objectives/Outcomes:
With respect ot dashboards in Tableau, students will:
begin to analyze the advantages and disadvantages of visualizations;
choose appropriate visualizations in order to effectively communicate a desired conclusion;
be able to create a Tableau dashboard in order to display multiple visualizations at once;
understand how to make their dashboards more interactive and accessible;
give feedback on a classmate’s Dashboard; and
revise their dashboards based on peer feedback and resubmit.
Learning Objectives/Outcomes:
Students will:
learn how to use color in data visualization, understand color vision deficiency, and learn options for designing colorblind-friendly data visualizations;
apply the principles of color choice in order to create a clear, attractive, CVD friendly Tableau dashboard;
understand visualization design principles and how the brain understands them in order to create visualizations that communicate a clear message;
be able to create an effective data visualization with multiple variables;
understand the different types of filters in Tableau and the order of operations needed to apply them appropriately; and
understand Tableau hierarchies and be able to create groups within Tableau.
Learning Objectives/Outcomes:
Students will be able to:
create calculated fields in order to create new variables formed by simple calculations;
create calculated fields in order to group data based on a specified range of values;
further analyze data through LoD calculations;
download multiple similar data sets and upload them into Tableau by creating data unions & data joins; and
communicate the difference between tidy and messy data.
Learning Objectives/Outcomes:
Students will:
learn to ask questions at the various levels of Bloom’s Taxonomy;
explore the 7 types of stories and learn how to construct a data story in Tableau;
create memorable titles for their visualizations and utilize the components of a story in order to improve their Superstore Story; and
review open data links and brainstorm their final project topic and question.