Response Changes Analysis: Original vs. Modified Frequencies
Response Changes Analysis: Visualizes response frequency changes when modifying key factors. Red bars show modified levels, green bars show unchanged values.
Scenario Testing
All-or-Nothing Simulator
Test scenarios where all respondents hold the same view
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Adjust these key factors from November 1963 to see how they might have affected presidential approval.
Get the original Harris/Newsweek Questionnaire (PDF)Understanding These Results
Contextual analysis based on your simulation
Predicted Probability
The predicted approval rate (-) comes from a logistic regression model. It estimates how likely someone would be to approve if they had the selected characteristics.
It also represents the expected approval rate for the entire population if everyone shared these same traits or responses. This probability reflects the model’s assumptions—not just raw survey percentages.
Confidence Interval
With a 95% confidence interval of -, we can be 95% confident that the model’s predicted probability lies within this range. This uncertainty range reflects how much the result might vary if the model were applied to a different random sample. A narrower interval indicates greater precision—not greater confidence.
Change from Baseline
The change from the baseline of 57% suggests some effect on the outcome. This represents a statistically non-significant change.
Practical Significance
In practical terms, this would translate to approximately - people more than the baseline expectation of 40 million. The change would be minimal in practical terms.
This analysis automatically adjusts based on your selected parameters. The results suggest this scenario would have maintained approval near historical levels.