Quantum XL Software Comparison
See how Quantum XL stacks up against competing statistical software, feature by feature.
| Pricing | |||||
|---|---|---|---|---|---|
| Feature | Quantum XL | Minitab | Crystal Ball | SPC XL | DOE Pro XL |
| Single license price | $649 one time |
$2,394 per year |
$1,210–$2,420 one time |
$299 one time |
$299 one time |
| Core Capabilities | |||||
| Design of Experiments | ✓ | ✓ | - | - | ✓ |
| General Statistical Tools | ✓ | ✓ | - | ✓ | - |
| Companion Tools (QFD, FMEA, Pugh) | ✓ | - | - | - | - |
| Monte Carlo Simulation | ✓ | - | ✓ | - | - |
| Control Charts | ✓ | ✓ | - | ✓ | - |
| Measurement System Analysis (MSA) | ✓ | ✓ | - | ✓ | - |
| Works inside Microsoft Excel | ✓ | - | ✓ | ✓ | ✓ |
| Perpetual license (no subscription) | ✓ | - | ✓ | ✓ | ✓ |
| DOE: Unique Features | |||||
| Regression Advisor | ✓ | - | - | - | - |
| Automatic S-hat Modeling | ✓ | - | - | - | ✓ |
| Mixed Response Modeling | ✓ | - | - | - | - |
| DOE: Regression Type | |||||
| Ordinary Least Squares | ✓ | ✓ | - | - | ✓ |
| Weighted Regression | ✓ | ✓ | - | - | - |
| Binary Logistic Regression | ✓ | ✓ | - | - | - |
| Nominal Logistic Regression | ✓ | ✓ | - | - | - |
| Ordinal Logistic Regression | - | ✓ | - | - | - |
| DOE: Optimization | |||||
| Optimize Least Squares Models | ✓ | ✓ | - | - | ✓ |
| Optimize Binary Logistic Models | ✓ | ✓ | - | - | - |
| Optimize Nominal Logistic Models | ✓ | ✓ | - | - | - |
| Optimize Mixed (LS, Binary, Nominal) Models | ✓ | - | - | - | - |
| Optimize with constraints | ✓ | - | - | - | - |
| DOE: Prediction | |||||
| Predict Least Squares Models | ✓ | ✓ | - | - | ✓ |
| Predict Binary Logistic Models | ✓ | ✓ | - | - | - |
| Predict Nominal Logistic Models | ✓ | ✓ | - | - | - |
| Predict Mixed (LS, Binary, Nominal) Models | ✓ | - | - | - | - |
| Quality Measures (Cp, Cpk, dpm, etc.) | ✓ | - | - | - | - |
| DOE: Charts | |||||
| Pareto of Regression Coefficients | ✓ | ✓ | - | - | ✓ |
| Interaction Plot | ✓ | ✓ | - | - | ✓ |
| Main Effect Plot | ✓ | ✓ | - | - | ✓ |
| Thumbnail Plot | ✓ | ✓ | - | - | ✓ |
| Surface and Contour Plot | ✓ | ✓ | - | - | ✓ |
| Residual Plots | ✓ | ✓ | - | - | ✓ |
| DOE: Design Types | |||||
| Design Wizard | ✓ | ✓ | - | - | ✓ |
| 2-Level Full/Fractional Factorial | ✓ | ✓ | - | - | ✓ |
| 3-Level Full Factorial | ✓ | ✓ | - | - | ✓ |
| N-Level (mixed) Factorial | ✓ | ✓ | - | - | - |
| Central Composite (CCD) | ✓ | ✓ | - | - | ✓ |
| Box-Behnken | ✓ | ✓ | - | - | ✓ |
| Plackett-Burman | ✓ | ✓ | - | - | ✓ |
| Taguchi | ✓ | ✓ | - | - | ✓ |
| Custom | ✓ | ✓ | - | - | ✓ |
| D-Optimal | ✓ | ✓ | - | - | - |
| Mixture | - | ✓ | - | - | - |
| DOE: Design Features | |||||
| Blocking | ✓ | ✓ | - | - | - |
| Folding | ✓ | ✓ | - | - | - |
| Automatic S-hat Model | ✓ | - | - | - | ✓ |
| Table Format | ✓ | - | - | - | ✓ |
| Stacked Format | ✓ | ✓ | - | - | - |
| Randomization | ✓ | ✓ | - | - | Random string only |
| Add Center Points | ✓ | ✓ | - | - | - |
| General Statistics: Data Template | |||||
| One factor | ✓ | - | - | - | - |
| Two factors | ✓ | - | - | - | - |
| Specification limits | ✓ | - | - | - | - |
| X-Axis column | ✓ | - | - | - | - |
| Random data | ✓ | - | - | - | - |
| Select multiple analyses on sheet | ✓ | - | - | - | - |
| Analyze template | ✓ | - | - | - | - |
| Control Charts | |||||
| XbarR Chart | ✓ | ✓ | - | ✓ | - |
| XbarS Chart | ✓ | ✓ | - | ✓ | - |
| IMR Chart | ✓ | ✓ | - | ✓ | - |
| p Chart | ✓ | ✓ | - | ✓ | - |
| c Chart | ✓ | ✓ | - | ✓ | - |
| np Chart | ✓ | ✓ | - | ✓ | - |
| u Chart | ✓ | ✓ | - | ✓ | - |
| Add points to existing charts | ✓ | ✓ | - | ✓ | - |
| Assign labels to X Axis | ✓ | ✓ | - | ✓ | - |
| Custom out-of-control checking | ✓ | ✓ | - | ✓ | - |
| Custom Control Limits | ✓ | ✓ | - | ✓ | - |
| On-sheet scrolling controls | ✓ | - | - | - | - |
| StDev estimate options | ✓ | ✓ | - | - | - |
| Scroll control charts | ✓ | ✓ | - | ✓ | - |
| Split limits | ✓ | ✓ | - | ✓ | - |
| Outliers | ✓ | ✓ | - | ✓ | - |
| Cpk / Process Capability | |||||
| Spec limits | ✓ | ✓ | - | ✓ | - |
| Spec limits linked to cell | ✓ | - | - | - | - |
| Spec limits are boundaries | ✓ | ✓ | - | - | - |
| Plot target value | ✓ | ✓ | - | - | - |
| Ppk curve | ✓ | ✓ | - | ✓ | - |
| Cpk curve | ✓ | ✓ | - | - | - |
| Both curves | ✓ | ✓ | - | - | - |
| Multiple charts | ✓ | ✓ | - | - | - |
| Overlaid charts | ✓ | ✓ | - | - | - |
| StDev estimate options | ✓ | ✓ | - | - | - |
| Cp, Cpl, Cpu, Cpk | ✓ | ✓ | - | - | - |
| CI bounds for Cp and Cpk | ✓ | ✓ | - | - | - |
| Pp, Ppl, Ppu, Ppk | ✓ | ✓ | - | ✓ | - |
| Observed / Short Term / Long Term Defects | ✓ | ✓ | - | ✓ | - |
| Sample size, Mean, StDev, Min, Max | ✓ | ✓ | - | ✓ | - |
| Updatable | ✓ | ✓ | - | - | - |
| Histogram | |||||
| Normal fit | ✓ | ✓ | - | ✓ | - |
| Exponential fit | ✓ | ✓ | - | - | - |
| Weibull, Gamma, Logistic, LogNormal fits (2 & 3 param) | ✓ | ✓ | - | - | - |
| 2-Parameter Weibull & Exponential fit | ✓ | ✓ | - | ✓ | - |
| Overlaid charts | ✓ | ✓ | - | - | - |
| Spec limits / linked to cell | ✓ | ✓ | - | - | - |
| Updatable | ✓ | ✓ | - | - | - |
| Scatter Plot | |||||
| Overlaid charts | ✓ | ✓ | - | - | - |
| Selectable X and Y columns | ✓ | ✓ | - | - | - |
| Linear / Log / Polynomial / Power / Exponential regression | ✓ | ✓ | - | ✓ | - |
| Extrapolate Model | ✓ | ✓ | - | ✓ | - |
| Regression analysis | ✓ | ✓ | - | - | - |
| On-sheet prediction | ✓ | - | - | - | - |
| Updatable | ✓ | ✓ | - | - | - |
| Pareto | |||||
| 2D / 3D columns with cumulative line | ✓ | ✓ | - | ✓ | - |
| Pareto report | ✓ | ✓ | - | ✓ | - |
| Max bars / 'Others' group / Custom caption | ✓ | ✓ | - | ✓ | - |
| Sort bars / Sort datasets | ✓ | ✓ | - | ✓ | - |
| Multiple / Grid of pareto charts | ✓ | ✓ | - | - | - |
| Updatable | ✓ | ✓ | - | - | - |
| Dot Plot & Box Plots | |||||
| Dot Plot - Multiple datasets | ✓ | ✓ | - | ✓ | - |
| Dot Plot - Two dimensional | ✓ | ✓ | - | - | - |
| Box Plot - Min, Max, Mean, Outliers | ✓ | ✓ | - | ✓ | - |
| Box Plot - Custom whiskers & box height | ✓ | ✓ | - | - | - |
| Updatable | ✓ | ✓ | - | - | - |
| Distribution Fit | |||||
| Normal, Exponential | ✓ | ✓ | - | - | - |
| 2-Param Weibull, Exponential, Gamma, Logistic, LogLogistic, LogNormal | ✓ | ✓ | - | - | - |
| 3-Param Gamma, LogNormal | ✓ | ✓ | - | - | - |
| Updatable | ✓ | ✓ | - | - | - |
| Multi-Vari Charts | |||||
| Mean, Median, Min, Max | ✓ | ✓ | - | - | - |
| Range line / Connect means | ✓ | ✓ | - | - | - |
| Group mean / Grand mean / StDev | ✓ | ✓ | - | - | - |
| Updatable | ✓ | ✓ | - | - | - |
| Hypothesis Tests | |||||
| Advisor Wizard | ✓ | ✓ | - | - | - |
| Auto Test | ✓ | - | - | - | - |
| One sample t-Test | ✓ | ✓ | - | ✓ | - |
| Two samples t-Test | ✓ | ✓ | - | ✓ | - |
| Paired t-Test | ✓ | ✓ | - | ✓ | - |
| One-way ANOVA | ✓ | ✓ | - | ✓ | - |
| Two-way ANOVA (Crossed & Nested) | ✓ | ✓ | - | - | - |
| F-test | ✓ | ✓ | - | ✓ | - |
| Levene's / Bartlett's test | ✓ | ✓ | - | - | - |
| 1-Sample Sign / 1-Sample Wilcoxon | ✓ | ✓ | - | - | - |
| Friedman / Mood's Median | ✓ | ✓ | - | - | - |
| Measurement System Analysis (MSA) | |||||
| ANOVA | ✓ | ✓ | - | ✓ | - |
| XbarR | ✓ | ✓ | - | ✓ | - |
| Nested ANOVA | ✓ | ✓ | - | ✓ | - |
| Attribute: Crosstabulation | ✓ | ✓ | - | ✓ | - |
| Attribute: Analytic method | ✓ | ✓ | - | - | - |
| Gage Performance Curve | ✓ | ✓ | - | - | - |
| Gage Linearity / Bias | ✓ | ✓ | - | ✓ | - |
| Stats Advisor | ✓ | - | - | - | - |
| Updatable | ✓ | ✓ | - | - | - |
| Reliability Tools | |||||
| Uncensored Parametric Analysis | ✓ | ✓ | - | - | - |
| Exact, Left, Right, Interval Censored | ✓ | ✓ | - | - | - |
| Maximum Likelihood Estimation | ✓ | ✓ | - | - | - |
| Goodness of Fit Measures | ✓ | ✓ | - | - | - |
| Reliability Plots: hazard, survival, pdf | ✓ | ✓ | - | - | - |
| MTBF and Percentile Analysis | ✓ | ✓ | - | - | - |
| Utilities & Data Tools | |||||
| Decision Trees | ✓ | - | - | - | - |
| DSM (Create, Edit, Navigate, Sequence) | ✓ | - | - | - | - |
| Component Swapping | ✓ | - | - | - | - |
| Stack / Unstack Columns | ✓ | ✓ | - | ✓ | - |
| SmartSelect | ✓ | - | - | ✓ | - |
| Random Number Generation | |||||
| Normal, Uniform, Triangular, Log-Normal | ✓ | ✓ | - | ✓ | - |
| Exponential, Weibull, Gamma, Logistic, Log-Logistic | ✓ | ✓ | - | - | - |
| Uniform Discrete, Poisson, Binomial, Binary | ✓ | ✓ | - | - | - |
| Chi-Square, F, t, Geometric, Hypergeometric, Integer | ✓ | ✓ | - | - | - |
| Beta, Cauchy, Laplace, Extreme Value | ✓ | ✓ | - | - | - |
| Table / Group By format / Generator per column | ✓ | ✓ | - | - | - |
| Other Features | |||||
| Excel data source | ✓ | ✓ | - | ✓ | - |
| 'Group by' data source | ✓ | ✓ | - | - | - |
| SQL data source | ✓ | ✓ | - | - | - |
| Discrete distribution calculator | Binomial | ✓ | - | ✓ | - |
| Continuous distribution calculator | Normal, Weibull | ✓ | - | ✓ | - |
| Main Effects Plot | - | ✓ | - | ✓ | - |
| Run Chart | ✓ | ✓ | - | ✓ | - |
| CUSUM Chart | - | ✓ | - | ✓ | - |
| CNX Template & Diagram | - | - | - | ✓ | - |
| Product Capability Report | ✓ | - | - | ✓ | - |
| Companion Tools: QFD | |||||
| QFD Wizard | ✓ | - | - | - | - |
| Create / Edit / Sort PCM Matrix | ✓ | - | - | - | - |
| Pareto PCM | ✓ | - | - | - | - |
| Create / Edit / Sort House of Quality | ✓ | - | - | - | - |
| Pareto HOQ | ✓ | - | - | - | - |
| Companion Tools: Pugh Matrix | |||||
| Create / Edit / Sort | ✓ | - | - | - | - |
| Create chart | ✓ | - | - | - | - |
| Companion Tools: FMEA | |||||
| Create matrix | ✓ | - | - | ✓ | - |
| Current process controls | ✓ | - | - | ✓ | - |
| Recommended actions / Action results | ✓ | - | - | ✓ | - |
| Add/Remove group, failure mode, failure cause | ✓ | - | - | - | - |
| Top 20 / Custom pareto | ✓ | - | - | - | - |
| Show/Hide columns | ✓ | - | - | - | - |
| Monte Carlo: Model Building | |||||
| IPO Sheets | ✓ | - | - | - | - |
| Import from DOE Pro | ✓ | - | - | - | - |
| Any cell can be input/output | ✓ | - | ✓ | - | - |
| Merge and Visual Merge | ✓ | - | - | - | - |
| Monte Carlo: Speed | |||||
| External calculation engine | Rocket Mode | - | Extreme Speed | - | - |
| Benchmark (1M simulations)* | 1.09 sec | - | 9.73 sec | - | - |
| Monte Carlo: Statistics | |||||
| Normal Distribution Stats | ✓ | - | ✓ | - | - |
| Count out of spec | ✓ | - | ✓ | - | - |
| Percentile Stats | ✓ | - | ✓ | - | - |
| Export EVA Raw Data | ✓ | - | ✓ | - | - |
| Monte Carlo: Features | |||||
| N=10K to 1 Million Simulations | ✓ | - | ✓ | - | - |
| Tolerance Allocation Table | ✓ | - | - | - | - |
| Latitude Plot | ✓ | - | - | - | - |
| Embedded Histograms | ✓ | - | ✓ | - | - |
| Percent Contribution | ✓ | - | ✓ | - | - |
| Descriptive Sampling Support | ✓ | - | - | - | - |
| Native Mode Monte Carlo | ✓ | - | ✓ | - | - |
| Input/Output Manager | ✓ | - | ✓ | - | - |
| Monte Carlo: Optimization | |||||
| Optimize single output | ✓ | - | Suite only | - | - |
| Reduce dpm across multiple outputs | ✓ | - | Suite only | - | - |
| Optimize on Cp, Cpk, Median, dpm, etc. | ✓ | - | Suite only | - | - |
| Optimize with constraints | ✓ | - | Suite only | - | - |
| Advanced Optimization Technology | ✓ | - | Suite only | - | - |
| Monte Carlo: Supported Distributions | |||||
| Normal, Exponential, Uniform, Triangular | ✓ | - | ✓ | - | - |
| Log-Normal, Logistic, Log-Logistic | ✓ | - | ✓ | - | - |
| Weibull (3-Param) | ✓ | - | ✓ | - | - |
| Uniform Discrete, Poisson, Binary, Binomial | ✓ | - | ✓ | - | - |
| Empirical / Custom Continuous / Custom Discrete | ✓ | - | ✓ | - | - |
| Monte Carlo: Sampling | |||||
| Latin Hypercube Sampling (LHS) | ✓ | - | ✓ | - | - |
| Descriptive Sampling | ✓ | - | - | - | - |
* Speed benchmark: 1,000,000 simulations on Crystal Ball example model "Cell Phone." Quantum XL is up to 9x faster than Crystal Ball.
Notes: Minitab price shown is for Minitab Solution Center Core (annual subscription). Crystal Ball base is $1,210; Suite (with Decision Optimizer) is $2,420; both are perpetual licenses. Prices verified as of March 2026; check vendor sites for current pricing.