StatLab — Statistical Calculator

Data Input ?How to enter data: Paste multiple numbers (e.g., DMFT scores) separated by commas, or type them one at a time. You can also click Random to try with sample data, or use a Dental Preset below.

💡 Quick start: Paste your dental data below (e.g., patient DMFT scores, probing depths, or plaque indices), or click a preset to load sample data instantly.

Dental Presets:

Separator: ?Choose how your numbers are separated. Most spreadsheet data uses commas or tabs. If you're pasting one number per line, choose "Newline". or add one at a time:

No data yet — enter numbers above or click a preset

Statistical Results ?What you'll see: After clicking Calculate, this section shows all key statistics — mean, median, standard deviation, quartiles, and more. Each colored card represents a different measure. These are the same statistics you'd report in a dental research paper!

↑ Enter data above and click Calculate

Distribution Chart ?What is this? A histogram showing how your data values are distributed across different ranges (bins). Taller bars mean more data points fall in that range. This helps you see if your data is symmetric, skewed, or has outliers — essential for choosing the right statistical test!

Enter data to visualize distribution

Hover over bars to see the range and count for each bin

Probability Calculators ?Probability tools help you calculate the likelihood of specific outcomes. These distributions (Normal, Binomial, Poisson) are commonly used in dental research to model patient data, treatment success rates, and event frequencies.

💡 Tip: Each calculator below solves a different type of probability problem. Hover over the ? icons next to each title for dental examples and explanations.

Normal Distribution (Z-score) ?Z-score tells you how many standard deviations a value is from the mean.

Dental example: If average plaque index is 1.5 (σ=0.4) and a patient scores 2.3, the Z-score = (2.3−1.5)/0.4 = 2.0, meaning they're 2 standard deviations above average — unusually high!

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Binomial Distribution P(X=k) ?Binomial calculates the probability of exactly k successes in n trials.

Dental example: If implant success rate is 92% (p=0.92), what's the probability that exactly 14 out of 15 implants succeed? Enter n=15, k=14, p=0.92.

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Poisson Distribution P(X=k) ?Poisson calculates the probability of k events occurring in a fixed interval when the average rate is λ.

Dental example: If a clinic sees an average of 3 emergency patients per day (λ=3), what's the probability of seeing exactly 5 emergencies today? Enter λ=3, k=5.

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Combination & Permutation ?C(n,r) = ways to choose r items from n (order doesn't matter). P(n,r) = arrangements (order matters).

Dental example: How many ways can you select 3 patients from a group of 10 for a clinical trial? C(10,3) = 120 ways.

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Percentage ↔ Decimal ↔ Fraction ?Why convert? Research papers report values differently. A p-value of 0.05 = 5%. Prevalence of 0.35 = 35%. This converter helps you switch between formats instantly.

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Logarithm Calculator ?Logarithms are used in statistics for log-transformations (making skewed data more normal) and in logistic regression. ln (natural log) uses base e ≈ 2.718. log₁₀ uses base 10.

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Power & Root ?Powers & roots are used in variance (squaring deviations) and standard deviation (square root). Enter exponent 0.5 for square root, 1/3 for cube root.

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Calculation History ?Every time you calculate statistics, the result is saved here. Click any entry to load that dataset back into the calculator. Useful for comparing results across different patient groups!

No history yet — calculate some statistics in the Descriptive tab to see them here

Statistical Formula Reference ?A quick-reference guide to the most commonly used formulas in dental biostatistics. Each card shows the formula, its name, and a plain-English explanation.

📐 Quick reference: These are the formulas used behind the scenes when you click "Calculate" in the Descriptive tab. Understanding them helps you interpret results in your dental research papers.

Mean

x̄ = Σxᵢ / n

Sum of all values divided by the count. The "average" — most common measure of central tendency.

Variance (Sample)

s² = Σ(xᵢ - x̄)² / (n-1)

Average squared deviation from the mean. Divides by (n-1) for sample data (Bessel's correction).

Std Deviation

s = √s²

Square root of variance; measures spread in the same units as your data (e.g., mm for probing depths).

Z-Score

z = (x - μ) / σ

How many standard deviations a value is from the mean. |Z| > 1.96 is significant at 95% confidence.

IQR

IQR = Q3 - Q1

Interquartile range — spread of the middle 50% of data. Robust against extreme outliers.

Coeff. of Variation

CV = (s / x̄) × 100

Relative variability as a percentage. Useful for comparing spread across different measurement scales.

Binomial P(X=k)

C(n,k) · pᵏ · (1-p)ⁿ⁻ᵏ

Probability of exactly k successes in n independent trials with success probability p.

Poisson P(X=k)

(λᵏ · e⁻λ) / k!

Probability of k events in a fixed interval when the average rate is λ (lambda).

🧮 Statistical Calculator