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CASE STUDIES · LIVE TOOLS · SHARED EXPLANATORY APPROACH

Case studies that show the
approach in action.

These live examples apply the Electric Insights workflow to two very different datasets: one in public opinion, one in sports analytics.

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2

Live Case Studies

9+

Interactive Tools Across Cases

2

Domains Demonstrated

1

Shared Modeling Workflow

Same structure, different domains

Each case study pairs a clearly defined outcome with explanatory modeling, interactive tools, source-data context, and scenario testing.

Outcome first

Each study starts with a concrete topline outcome: presidential approval in one case, three-point make rate in the other.

Drivers and scenarios

The tools show what measured factors help explain the result and how the outcome changes under alternative conditions.

Visible source context

Each case includes domain background, source-data framing, and live entry points into the underlying analytical tools.

Browse the live studies

Start with the domain that interests you most, or compare the two to see how the same underlying approach travels.

Public Opinion

JFK Approval

In November 1963, 57% of Americans approved of President Kennedy. The case study asks what drove that number and what might have changed it.

Dataset

Harris/Newsweek survey

Main outcome

Presidential approval

Tool pattern

Explorer + simulators + model builder

Best for

Public-opinion interpretation

  • Historical and political context for the original survey
  • Interactive tools for scenario testing and inspection
  • Direct path from descriptive record to explanatory analysis
View JFK Case Study Launch JFK Tool
Sports Analytics

NBA 3-Point Shots

In the 2014–15 NBA season, players made about 35% of their three-point attempts. The case study asks what shot conditions drove that rate and what might have changed it.

Dataset

SportVU shot logs

Main outcome

Three-point make rate

Tool pattern

Explorer + simulators + model builder

Best for

Shot-condition analysis

  • Season and data-provenance framing for the SportVU sample
  • Multiple ways to simulate shot-condition changes
  • Direct comparison of exploration, tuning, and model-building paths
View NBA Case Study Launch NBA Tool

What the studies have in common

Each case study follows the same broad sequence from outcome to explanation to scenario testing.

1

Start with the outcome

A visible topline anchors the study and gives users a concrete entry point.

2

Inspect the source data

Users can move from descriptive distributions to more focused analytical questions.

3

Model the drivers

The explanatory layer makes it easier to see what measured factors matter under stated rules.

4

Test scenarios

Interactive tools let users see how outcomes change when conditions are altered.

Quick comparison

Different subject matter, same core architecture.

Dimension JFK NBA
Domain Public opinion Sports analytics
Topline outcome Presidential approval Three-point make rate
Source period November 1963 2014–15 NBA season
Typical user questions What drove support, and what might have changed it? What shot conditions drove accuracy, and what might have changed it?
Interactive emphasis Public-facing explanation and scenario testing Shot-condition exploration and simulation

Start with the case that interests you most

Both studies are live. Browse the background first, or jump straight into a tool.

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