Searching Our Collective Consciousness A Google Trends Activity for Introductory Students Eric...
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Searching Our Collective Consciousness A Google Trends Activity for Introductory Students Eric Nordmoe Department of Mathematics and Computer Science
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Transcript of Searching Our Collective Consciousness A Google Trends Activity for Introductory Students Eric...
Searching Our Collective ConsciousnessA Google Trends Activity for
Introductory Students
Eric NordmoeDepartment of Mathematics and Computer Science
How do we engage our students in statistical thinking?
Classroom activities should be…
• Real• Engaging• Conceptual• Thought-provoking• Purposeful
Typical classroom activities
• Hands-on activities– Gelman & Nolan, 2002
• Real-world data sets– Dawson, JSE95; Hayden, JSE05; Hand, 1994
• Simulation-based learning– DelMas & Garfield, JSE99
A brief history of Google Trends
Google Insights for Search
Google Trends
GoogleFlu Trends
May 06: Plot popularity of search terms
Aug 08: In-depth analysis by category and geography
Nov 08: Produce early-warningestimates of flu activity (Ginsberg et al., Nature2008)
Back
Back
The Google Insights for Search interface
Query “index” scaled against maximum in Feb 2008
Search parameters
Emphasizes context
Downloadable data file
The Google Trends Activity
• Analysis of a simplified flu trends data set – Weekly data Jan 04-May 08– 230 cases, 6 variables
Estimated % of outpatient
visits showing flu-like symptoms
fever
“cold symptoms”
“flu symptoms”
query #4
Responsevariable
Explanatory queryvariables
The Google Trends Activity:
The Variables
The Google Trends Activity:Overview
Background
Univariate description
Bivariate description
Reflection & extensions
Time-based description
The Google Trends Activity:
A Quick Look
r =.94 r =.87
r =.61 r =.76
Learning Outcomes
• Mastery of tools for data description
• Sensitivity to unique characteristics of time series data
• Development of critical, statistical thinking skills
• Opportunities to formulate hypotheses
Suggestions for Classroom Use
• Introductory Statistics• 1-2 class sessions• Integrates univariate and bivariate learning
• Requires stats software
Cautions
• No random sampling model• Serial correlation• Index (scaled) data
Extensions
• Transformations– logit
• Hypothesis testing– Between geographic subregions, years, etc.
• Regression models– Interpretation, assumptions and diagnostics
• Time series analysis– Significance testing– Seasonality
Questions?
Google Trends Activity Links
• Google Trends Activity– Word .doc file http://tinyurl.com/nk2uo2
• Downloadable data files– Excel .xls file http://tinyurl.com/ly3s8c– SPSS .sav file http://tinyurl.com/mbdpw2
