Big Data, Graphs, and Prediction

Name: Big Data, Graphs, and Prediction
Published: 2021-02-17
License: CC Attribution-ShareAlike 4.0 International

Jennifer Lyon Adler; David Simon; Emmanuel des-Bordes; Joseph Esquibel; mary miller; Pradip Raj Aryal; Vickie Flanders

doi:10.25334/6QDH-4T19

Big Data, Graphs, and Prediction

By Jennifer Lyon Adler¹, David Simon², Emmanuel des-Bordes³, Joseph Esquibel⁴, mary miller², Pradip Raj Aryal⁵, Vickie Flanders²

1. Maysville Community and Technical College 2. Baton Rouge Community College 3. Blue Ridge Community College 4. University of Wisconsin - Madison, Madison College 5. NMSU Carlsbad

In this activity, students are introduced to graphing and modeling data in a step-wise fashion. Real data of covid-19 deaths over time are used to incrementally ask students to fit the data to several models and discuss which model fits best.

Listed in Teaching Materials | resource by group The BioGraphers - A QB@CC Incubator group

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Description

Big Data, Graphs, and Predictions was developed as part of an effort by the Quantitative Biology at Community Colleges group to provide materials that incorporate mathematical concepts into biology courses. The activity presents a process of systematic process of graphing, modelling and interpreting data, and making subsequent predictions. Given data will be compared with common trend curves. The activity is applicable for the College Algebra (Algebra II) courses.

After completing this module, students will be able to:

Learn how to interpret data and make a scatterplot
Comprehend the common trend curves and their use in interpreting data sets
Interpret complex data sets
Be familiar with the benefits and drawbacks of various graph types
Graph data sets and compare resulting charts to trend lines
Use various methods to make predictions.

“This material is based upon work supported by the National Science Foundation under Grant No. 1919613. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.”