Binary Logistic Regression Calculator
Model the probability of a binary outcome, such as pass/fail or disease/healthy, from one or more predictors. Coefficients are converted to odds ratios with confidence intervals.
Updated · By Bibin XavierData 90 × 12
| IDtext · 90 levels | Grouptext · 3 levels | Gendertext · 2 levels | Agenumeric | Hours_Studynumeric | Anxietynumeric | Motivationnumeric | Pre_Scorenumeric | Post_Scorenumeric | Exam_Scorenumeric | Passednumeric · coded | Satisfactionnumeric · coded |
|---|---|---|---|---|---|---|---|---|---|---|---|
| S001 | Control | Male | 23 | 11.2 | 29 | 4.6 | 60 | 62 | 67 | 1 | 2 |
| S002 | Workshop | Female | 23 | 3.9 | 28 | 3.5 | 54 | 70 | 54 | 0 | 2 |
| S003 | Online | Female | 18 | 10.1 | 32 | 4 | 55 | 57 | 66 | 0 | 3 |
| S004 | Control | Male | 26 | 13.6 | 41 | 3.5 | 52 | 55 | 59 | 0 | 3 |
| S005 | Workshop | Female | 22 | 9.7 | 27 | 3.6 | 56 | 63 | 65 | 0 | 4 |
| S006 | Online | Female | 20 | 7.9 | 32 | 3.8 | 65 | 82 | 65 | 0 | 2 |
| S007 | Control | Female | 20 | 6.3 | 28 | 3 | 72 | 83 | 61 | 0 | 3 |
| S008 | Workshop | Male | 22 | 8 | 29 | 3.1 | 64 | 72 | 62 | 1 | 3 |
Variables and options
Results
90 rows · example dataVariables in the equation
| Predictor | B | SE | Wald | p | Odds ratio | 95% CI for OR |
|---|---|---|---|---|---|---|
| Hours_Study | 0.344 | 0.111 | 9.63 | .002 | 1.410 | [1.135, 1.752] |
| Anxiety | -0.094 | 0.037 | 6.36 | .012 | 0.910 | [0.846, 0.979] |
| Pre_Score | 0.077 | 0.032 | 5.75 | .016 | 1.080 | [1.014, 1.151] |
| (Constant) | -6.076 | 2.587 | 5.51 | .019 | 0.002 |
Note. Event = “1” (31 of 90). Cox & Snell R² = .207, McFadden R² = .180. Hosmer-Lemeshow χ²(8) = 5.46, p = .708 (adequate fit).
Classification table (cut-off 0.50)
| Observed | Predicted 0 | Predicted 1 | % correct |
|---|---|---|---|
| Not event | 52 | 7 | 88.1 |
| Event (1) | 18 | 13 | 41.9 |
| Overall | 72.2 |
Odds ratios with 95% CI
Interpretation
The model predicts Passed better than chance and classifies 72.2% of cases correctly. Each one-unit increase in Hours_Study multiplies the odds of the event by 1.41 (a 41% increase). Each one-unit increase in Anxiety multiplies the odds of the event by 0.91 (a 9% decrease). Each one-unit increase in Pre_Score multiplies the odds of the event by 1.08 (a 8% increase).
How to cite this tool
Using these results in a thesis, journal article, report or class assignment? Please cite this free tool so others can find it. It keeps the site free.
APA 7
Xavier, B. (2026). Binary Logistic Regression Calculator [Web application]. FreeStatisticalTools.com. https://freestatisticaltools.com/logistic-regression-calculator/
BibTeX
@software{xavier_logisticregression_2026,
author = {Xavier, Bibin},
title = {Binary Logistic Regression Calculator},
publisher = {FreeStatisticalTools.com},
year = {2026},
url = {https://freestatisticaltools.com/logistic-regression-calculator/},
note = {Web application}
}Suggested sentence for your methods section: “The analysis was carried out with the free Binary Logistic Regression Calculator tool on FreeStatisticalTools.com (Xavier, 2026).”
What is logistic regression?
Binary logistic regression models the probability of a yes/no outcome from one or more predictors. Coefficients are reported as odds ratios with confidence intervals, alongside model fit statistics and a classification table.
When to use logistic regression
Use it when the outcome has two categories and you want to know which predictors raise or lower the odds of the event.
Assumptions
- A binary outcome and independent observations.
- A linear relationship between continuous predictors and the log odds.
- No severe multicollinearity, and at least about 10 events per predictor.
How to use this tool
- Enter your data. Paste columns from Excel, Google Sheets or SPSS with variable names in the first row, or upload a CSV or Excel file. The example data shows the expected layout.
- Choose the variables. Select the binary outcome, event (coded 1) and predictors.
- Read the results. Results update automatically. Read the plain-English interpretation, then use Copy table to paste APA-style tables into Word and Copy for the results sentence.
How to report logistic regression in APA style
Report the omnibus χ², Nagelkerke R², and for each predictor B, SE, Wald, p and the odds ratio with its 95% CI.
Frequently asked questions
How do I interpret an odds ratio?
An odds ratio of 1.5 means each one-unit increase in the predictor multiplies the odds of the event by 1.5, a 50% increase. Values below 1 mean lower odds.
Which pseudo R² should I report?
Nagelkerke R² is the most commonly reported, often alongside Cox and Snell. They are not directly comparable with R² from linear regression.
What does a significant Hosmer-Lemeshow test mean?
A p-value below .05 suggests the model’s predicted probabilities do not match the observed outcomes well.
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