Dataset
| Index | Value | Keep? | Action |
|---|
Controls
Results
Formula used
For a finite dataset \( S = \{x_1, \dots, x_n\} \), the absolute (global) minimum is
With constraints:
Tie-handling:
Outliers (optional) may be excluded by the IQR whisker rule defined as \([Q_1 - k\cdot IQR,\; Q_3 + k\cdot IQR]\).
How to use this calculator
- Paste, upload, or generate numbers to fill the table.
- Optionally set bounds, sorting, and outlier exclusion.
- Choose precision, index base, ties, and duplicate handling.
- Press Compute Minimum to update results.
- Add a dataset label and notes, then export CSV or PDF.
Example data table
This example includes duplicates, negatives, and zeros to illustrate tie-handling, bounds, and outlier exclusion.
| # | Value | Included |
|---|---|---|
| 1 | -3 | Yes |
| 2 | 7 | Yes |
| 3 | 0.5 | Yes |
| 4 | -3 | Yes |
| 5 | 4 | Yes |
| 6 | -10 | Yes |
| 7 | 2.1 | Yes |
Common use cases & domains
| Domain | Example variable | Why minimum matters |
|---|---|---|
| Manufacturing | Defect count per batch | Find best-performing run |
| Finance | Daily return (%) | Identify worst-case loss |
| Operations | Lead time (days) | Benchmark fastest supplier |
| Quality | Tolerance deviation | Find closest-to-spec item |
| Web | Page load (ms) | Track fastest experience |
Sample datasets and minima
| Dataset | Values | Absolute minimum | Indices |
|---|---|---|---|
| A | 5, 2, 9, 2, 7 | 2 | 2, 4 |
| B | -4, -1, 3, 0 | -4 | 1 |
| C | 0.4, 0.2, 0.2 | 0.2 | 2, 3 |
| D | 12 | 12 | 1 |
| E | 8, 6, 7 | 6 | 2 |
Complexity, limits, and performance
| Metric | Value | Notes |
|---|---|---|
| Time complexity | O(n) | Single pass scan for minimum |
| Memory overhead | O(1) | Streaming-friendly computation |
| Recommended rows | ≤ 100,000 | Browser memory dependent |
| Precision range | 0–8 decimals | User-selectable formatting |
| CSV size | ~5 MB | Above this may lag UI |
Validation, rounding, and edge cases
| Rule | Behavior | Example |
|---|---|---|
| Non-numeric entries | Ignored if enabled | "abc", "", NaN removed |
| Bounds filter | Exclude outside [L,U] | L=-5, U=3 keeps -4, 0, 2 |
| Tie mode | All / first / last | 2,1,1,3 → indices 2,3 or 2 or 3 |
| Duplicates off | Unique values only | 2,2,1 → treat as 2,1 |
| IQR exclusion | Remove outliers | k=1.5 typical Tukey whisker |
Frequently Asked Questions
1) What is an absolute minimum?
The absolute minimum is the smallest value in a dataset or the lowest function value on a specified interval. It represents the global minimum, not just a local dip.
2) How are ties between equal minima handled?
You can return all indices, only the first, or only the last. Choose your preferred tie mode in Controls, and the results update accordingly for transparent reporting and reproducibility.
3) What happens to non‑numeric entries?
Enable “Ignore non-numeric entries” to automatically exclude invalid cells such as blanks or text. Disable it if you need strict validation and want to detect problematic values explicitly during review.
4) How do bounds affect the minimum?
Values outside the lower and upper bounds are excluded before computing the minimum. This allows you to focus on a relevant operating range or remove physically impossible or out-of-spec readings.
5) What is IQR outlier exclusion?
When enabled, the tool removes values outside [Q1 − k·IQR, Q3 + k·IQR]. Adjust k to control strictness. This helps limit extreme outliers from dominating results while preserving central, representative behavior.
6) Does sorting change indices or the answer?
Sorting only affects display and export order. Original indices remain intact, so the reported positions of minima are consistent with the dataset’s original structure, ensuring accurate traceability.
7) How do I export properly formatted results?
Use “Download CSV” for spreadsheets and “Download PDF” for shareable reports. The PDF includes settings, results, and an optional notes section for quick documentation and audit-friendly context.