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Online Poll Bias Estimator

Online Poll Bias Estimator calculates bias score, reliability, and margin of error from sample size, response rate, and platform for accurate poll analysis.

Formulas Used in Online Poll Bias Estimator

The calculator uses the following formulas to estimate poll bias:

Bias Score:

\\[ B_s = \min\left(100 \cdot \frac{S_b}{R \cdot M_p}, 100\right) \\]

Sample Reliability:

\\[ R_s = \min\left(100 \cdot \frac{N \cdot R}{N_{\text{max}}}, 100\right) \\]

Margin of Error:

\\[ M_e = \frac{1.96}{\sqrt{N \cdot R}} \cdot 100 \\]

Where:

  • \\( B_s \\): Bias score (%)
  • \\( S_b \\): Selection bias factor (decimal)
  • \\( R \\): Response rate (decimal)
  • \\( M_p \\): Platform type multiplier (Social Media: 1.2, Email: 1.0, Website: 0.8)
  • \\( R_s \\): Sample reliability (%)
  • \\( N \\): Sample size (people)
  • \\( N_{\text{max}} \\): Maximum reference sample size (10000)
  • \\( M_e \\): Margin of error (%)

Example Calculations

Example 1: Small Poll, High Bias, Social Media

Input: Sample Size = 100, Response Rate = 20%, Selection Bias Factor = 30%, Platform Type = Social Media

\\[ B_s = \min\left(100 \cdot \frac{S_b}{R \cdot M_p}, 100\right) = \min\left(100 \cdot \frac{0.3}{0.2 \cdot 1.2}, 100\right) = 100 \ \% \\] \\[ R_s = \min\left(100 \cdot \frac{N \cdot R}{N_{\text{max}}}, 100\right) = \min\left(100 \cdot \frac{100 \cdot 0.2}{10000}, 100\right) = 0.2 \ \% \\] \\[ M_e = \frac{1.96}{\sqrt{N \cdot R}} \cdot 100 = \frac{1.96}{\sqrt{100 \cdot 0.2}} \cdot 100 = 43.84 \ \% \\]

Result: Bias Score: 100%, Sample Reliability: 0.2%, Margin of Error: 43.84%

Example 2: Medium Poll, Moderate Bias, Email

Input: Sample Size = 500, Response Rate = 40%, Selection Bias Factor = 15%, Platform Type = Email

\\[ B_s = \min\left(100 \cdot \frac{S_b}{R \cdot M_p}, 100\right) = \min\left(100 \cdot \frac{0.15}{0.4 \cdot 1.0}, 100\right) = 37.5 \ \% \\] \\[ R_s = \min\left(100 \cdot \frac{N \cdot R}{N_{\text{max}}}, 100\right) = \min\left(100 \cdot \frac{500 \cdot 0.4}{10000}, 100\right) = 2 \ \% \\] \\[ M_e = \frac{1.96}{\sqrt{N \cdot R}} \cdot 100 = \frac{1.96}{\sqrt{500 \cdot 0.4}} \cdot 100 = 13.86 \ \% \\]

Result: Bias Score: 37.5%, Sample Reliability: 2%, Margin of Error: 13.86%

Example 3: Large Poll, Low Bias, Website

Input: Sample Size = 2000, Response Rate = 60%, Selection Bias Factor = 5%, Platform Type = Website

\\[ B_s = \min\left(100 \cdot \frac{S_b}{R \cdot M_p}, 100\right) = \min\left(100 \cdot \frac{0.05}{0.6 \cdot 0.8}, 100\right) = 10.42 \ \% \\] \\[ R_s = \min\left(100 \cdot \frac{N \cdot R}{N_{\text{max}}}, 100\right) = \min\left(100 \cdot \frac{2000 \cdot 0.6}{10000}, 100\right) = 12 \ \% \\] \\[ M_e = \frac{1.96}{\sqrt{N \cdot R}} \cdot 100 = \frac{1.96}{\sqrt{2000 \cdot 0.6}} \cdot 100 = 5.66 \ \% \\]

Result: Bias Score: 10.42%, Sample Reliability: 12%, Margin of Error: 5.66%

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