Phi Coefficient Calculator
Determine the degree of association between two binary categorical variables using our Phi Coefficient Calculator. Simply input your datasets consisting of 0s and 1s to instantly calculate the coefficient and understand the correlation.
Input Data
Enter your binary categorical data (0 or 1) for Variable 1 and Variable 2, separated by commas.
Result: Phi Coefficient
Visualization & Interpretation
Contingency Table
| Variable 1 \ Variable 2 | Value = 1 | Value = 0 |
|---|---|---|
Value = 1 | ||
Value = 0 |
Interpretation of Phi Coefficient
The Phi coefficient is a measure of association between two binary categorical variables. It ranges from -1 to +1, where:
- 接近 +1: Strong positive association. As one variable increases (or is 1), the other tends to increase as well.
- 接近 -1: Strong negative association. As one variable increases (or is 1), the other tends to decrease (or be 0).
- 接近 0: Little to no association between the variables.
Your calculated Phi coefficient is .
Understanding Phi Coefficient
The Phi coefficient, denoted as φ, is used in statistics to measure the association between two binary variables. Binary variables are those that can take only two values, often represented as 0 and 1, true or false, or yes or no. The Phi coefficient is essentially a Pearson correlation coefficient applied to binary data.
It is particularly useful in scenarios where you need to understand if there's a relationship between two categorical variables that have only two possible outcomes. For example, in medical studies to see if a treatment (yes/no) is associated with recovery (yes/no), or in marketing to check if exposure to an ad (yes/no) is related to purchase (yes/no). The value of Phi ranges from -1 to +1, providing a clear direction and strength of association.
Formula: φ = (ad - bc) / √((a+b)(c+d)(a+c)(b+d)) , where a, b, c, d are the counts in a 2x2 contingency table.
Learn more about Phi Coefficient on Wikipedia and other statistical resources.