Basic Statistics

• Graphical Summary, which includes the Anderson-Darling normality test and descriptive statistics.

• 1t-One-sample t-test. Considering the alternative hypothesis variations:

  • mean < hypothetical mean

  • mean > hypothetical mean

  • mean ≠ hypothetical mean

• 2t - 2 -sample t test. Considering data input, Data is in the same column and Data is in different columnsConsidering the alternative hypothesis variations:

  • average G1 < average G2

  • G1 average > G2 average

  • G1 mean ≠ G2 mean

• Paired t-test (BB).

• 2P Test for two Proportions: with normal approximation and Fisher's exact test (BB)

• 2-variance test. F test for equality of two variances.

• Anderson-Darling Normality Test, simple or open by groups.

• Fitted line plot. Simple regression (linear, quadratic and cubic) with scatterplot and fitted line.

ANOVA

• Test for Equal of Variance

  • Bartlett test

  • Levene's Test (BB)

• One-way Anova. Considering data input

  • Data is in the same column

  • Data is in different columns

  • Post-Tukey test

Non-Parametric

• Mood test for median (BB)

Table​

• Chi-Square: Test of Independence

• Chi-square Goodness of fit (one variable) (BB)

Control Charts

• I-MR

• Xbarra-R

• Xbarra-S

• P

• np

• C

• U

Quality tools

• Run Chart. Simple time series

• Pareto's chart. Considering data input

  • Attribute data for which frequencies should be calculated

  • Attribute data that must be counted with the already calculated frequencies

• Capability Analysis (normal). Calculates Zbench and DPMO or Pp and Ppk considering data input in a column or historical data with the mean and standard deviation. Capacity analysis by subgroups is also available, generating Zbench and DMPO (inside) as well as Cp and Cpk statistics.​

Graphics​

• Boxplot

• Scatter diagram

• Normal probability distribution graph.

​Data

• Split Worksheet

• Stack data

Templates

• FMEA Template

• Cause and Effect Matrix Template

• Attribute process capacity calculation template