Data Analysis and Visualization

Arizona State University (ASU)
Tempe, Arizona, United States
Assistant Professor
2
Timeline
  • March 25, 2022
    Experience start
  • March 30, 2022
    Project Scope Meeting
  • May 1, 2022
    Experience end
Experience
1/3 project matches
Dates set by experience
Preferred companies
Anywhere
Any
Science

Experience scope

Categories
Data analysis
Skills
presentation professional communication statistics consulting biological sciences
Learner goals and capabilities

Students from Arizona State University's "Practical Data Analysis and Visualization using R" course will work with your organization to spot trends and relationships inside any large data set. Students will submit their recommendations and conclusions to decision-makers of the company.

Learners

Learners
Undergraduate
Any level
50 learners
Project
25 hours per learner
Learners self-assign
Teams of 3
Expected outcomes and deliverables

The final report will include:

  • A brief summary of important and insightful information discovered from the available data
  • Tables and graphs of important statistics and relationships
  • A brief summary of conclusions and any recommendations based on the data and information obtained
Project timeline
  • March 25, 2022
    Experience start
  • March 30, 2022
    Project Scope Meeting
  • May 1, 2022
    Experience end

Project Examples

Requirements

Using real data from your organization, students will identify trends and relationships inside large data sets, create presentation-style graphs and tables, and submit their recommendations and conclusions to decision-makers of the company (companies geared towards the biological sciences preferred).

Groups of students will use your data to:

  • Analyze your data to spot trends and relationships among variables
  • Create tables and graphs of summary statistics of key variables
  • Create a summary of conclusions in a document that quickly and efficiently conveys information the company may find interesting or important
  • Test whether different products or groups of individuals have different outcomes or preferences, and whether these differences are large enough to benefit from different strategies

Possible project examples include, but are not limited to:

  • Analysis of sales data to determine the relationship between your products' or services' price and volume of sales
  • Identifying patterns in sales or usage-based on seasonality
  • Creating a summary of key customer demographic statistics
  • Summarizing results of a customer survey to identify which characteristics are associated with different preferences

Additional company criteria

Companies must answer the following questions to submit a match request to this experience:

  • Q - Checkbox
  • Q - Checkbox