Inicio » Simplifica tus cálculos con facilidad. » Calculadoras estadísticas » Calculadora de diferencia de proporciones

Calculadora de diferencia de proporciones

Muestra tu amor:
0

The Difference in Proportions Calculator helps determine the statistical significance of the difference between two proportions from independent samples. This tool is widely used in evaluación de la hipótesis, investigación de mercado, por trials, and social sciences to compare categorical data across different groups. By computing the Z-score, users can assess whether the observed difference in proportions is statistically significant or due to random variation.

Formula of Difference In Proportions Calculator

The formula to calculate the Z-score for the difference in proportions is:

Vea también  Calculadora de límite de error

Difference In Proportions

dónde:

  • p1 is the proportion from the first group (x1 / n1)
  • p2 is the proportion from the second group (x2 / n2)
  • n1 is the sample size of the first group
  • n2 is the sample size of the second group
  • x1 and x2 are the number of successes in each group

Esta fórmula calcula la desviación estándar of the difference in proportions and determines the Z-score, which helps in hypothesis testing.

Difference in Proportions Reference Table

This table provides common values for statistical testing and comparison across different sample sizes.

Sample Size (n1 = n2)Proportion 1 (p1)Proportion 2 (p2)Puntuación Z
1000.500.450.72
2000.600.502.23
5000.550.501.77
10000.700.652.20
20000.800.752.74

These values provide a reference for understanding how different proportions and sample sizes affect statistical significance.

Vea también  Calculadora V de Cramer

Example of Difference In Proportions Calculator

A researcher wants to compare the proportion of customers who prefer two different product designs. Out of 500 customers surveyed for design A, 55% preferred it, while out of 500 customers surveyed for design B, 50% preferred it.

Usando la fórmula:

Z = (0.55 – 0.50) / √[(0.55(1 – 0.55) / 500) + (0.50(1 – 0.50) / 500)]

After calculating, the Z-score is approximately 1.77, which suggests that the difference is close to statistical significance at the 0.05 level.

Preguntas frecuentes más comunes

How do I interpret the Z-score in proportion testing?

A higher absolute Z-score (typically above 1.96 for a 95% confidence level) suggests a statistically significant difference between the two proportions.

Can this calculator be used for A/B testing?

Yes, the Difference in Proportions Calculator is frequently used in A/B testing to analyze the effectiveness of different marketing strategies, website designs, and other business experiments.

Deja un comentario