Develve has no deep hidden menus, everything is directly accessible and the results are directly visible, to improve the productivity.
•Sample counting n
•Full version of Develve 75Euro Update License 25Euro
Small (<50 employees), Medium (50 to 1000 Enterprise (>1001 employees)
• Variation F-test
• Variation Levene test
• Anderson Darling normality test
• Correlation test
• Tests normally distributed data
• Test non normal distribution data
• Measures system analyses
• Offers a statistical handbook
Develve is a statistical software for fast and easy interpretation of experimental data in science and R&D in a technical environment. Develve helps with analysis and prevents making false assumptions.
In short it makes statistics faster and easier, suitable for less experience users but advanced enough for more demanding users. Develve has no deep hidden menus, everything is directly accessible and the results are directly visible, to improve the productivity.
For instance the result graphs are easily scrollable and with a click on a graph a bigger version will pop up. Develve clearly indicates when two variables are significantly different, and if the sample size is big enough to prevent false assumptions.
For a Design of Experiments Develve helps to create a test matrix. When a factor is not in balance Develve will detect this. Develve can help to develop a robust product with high quality, this makes Develve an excellent six sigma toolbox. The Six Sigma methodology is used to get the quality level at the highest level.
It is discipline and data driven approach to minimize defects in a production process. With the Six Sigma failure level as goal 3.4 defects Parts per Million (PPM). The 3.4 PPM is 4.5 Sigma Long term and considered 6 Sigma Short term. The six sigma tools supported by Develve are Cp Cpk % out of tolerance, Regression analysis, Correlation, One way Anova, Gauge R&R measurement system analyses, Chi Square test respectively. Develve also supports a variety of graphs such as Histogram, Control Chart, Scatter Correlation plot , Time series plot ,Individual dot plot.