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Weighting

Plan poll weights, calculate from sample and benchmark counts, and interpret the impact.

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For poll researchers deciding how to weight a sample, compare candidate variables such as age, region, education, or past vote against your target population. Work through a weighting calculation from counts you paste, then compare weighted and unweighted estimates and discuss effects on interpretation and uncertainty. Leave with a weighting plan, worked calculation, and reporting cautions based on your study design.

What it writes

  • Poll weighting plan and variable trade-offs
  • Worked sample-to-benchmark weight calculation
  • Weighted-results interpretation and reporting cautions

How to use it

In your first message, name the target population and sampling method, then paste sample counts and matching benchmark totals with category labels. That lets the plan address real imbalances and show its assumptions.

This workspace provides text assistance.

What you bring

  • Poll design and target population
  • Sample counts and population benchmarks
  • Variable definitions and existing weighting rules
  • Paste figures directly into chat

A good fit for

  • Choosing demographic weighting variables for a poll with sample imbalances
  • Calculating weights from survey counts and population benchmark totals
  • Explaining how weighting changes poll estimates and their interpretation

Ways to start

A few requests this Agent can handle.

My poll has 800 respondents, but younger adults are underrepresented. The target population is adults in Ohio. Which benchmarks should I consider, and what trade-offs matter?

Sample counts are 120, 240, and 140 across three age groups; population shares are 25%, 45%, and 30%. Show the basic weights and assumptions.

My governor poll is 48% for Candidate A unweighted and 45% weighted after education and age adjustments. Explain what changed and what I should report.

What this Agent does not do

It does not carry out actions in other applications.

  • Validated analysis of inaccessible survey datasets
  • Guarantees of representative results or corrected bias
  • Statistical advice for high-stakes decisions
  • Calculations rely on figures pasted into chat
  • Cannot inspect survey files or validate your sampling design

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What if the response is not right for me?

Payments are generally non-refundable after access is activated, including for disliked, inaccurate, or unsuitable responses. Cancellation stops future renewals; it does not request a refund. Your legal rights still apply. Read the billing and cancellation policy

Can I use the response in my work?

Use it as a draft to review and adapt. Verify calculations, facts, rights, and suitability before relying on it. Do not provide information you do not have permission to share.

Can I paste work or client information?

Your request and relevant context are sent to the enabled AI service to generate a response. Use placeholders and share only the minimum information you have permission to send. Avoid confidential, regulated, highly sensitive, or unnecessary personal information; removing names alone does not make restricted material suitable. Review the Privacy Policy before sharing work

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Sign in with the account used for the purchase and review your existing order in Account & Billing. Contact support with your account email, order number, Agent name, and a short description of the issue before buying again. Do not send passwords, payment-card details, or confidential prompts. Contact support

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