# Analysis capture tool templates

You can use the following analysis capture tool templates as they are, or you can customize them.
Analysis capture tool Description of the statistical analysis Menu path in Minitab
1 Proportion Computes a confidence interval and performs a hypothesis test of the proportion. Stat > Basic Statistics > 1 Proportion
1 Variance Test Computes confidence intervals for the standard deviation and variance of a population and performs a hypothesis test of the variance. Stat > Basic Statistics > 1 Variance
1-Sample Sign Performs a hypothesis test of the median or calculates the corresponding point estimate and confidence interval. Stat > Nonparametrics > 1-Sample Sign
1-Sample t Computes a confidence interval and performs a hypothesis test of the mean when the standard deviation of the population is unknown. Stat > Basic Statistics > 1-Sample t
1-Sample Wilcoxon Performs a signed rank test of the median or calculates the corresponding point estimate and confidence interval. Stat > Nonparametrics > 1-Sample Wilcoxon
2 Proportions Computes a confidence interval and performs a hypothesis test of the difference between two proportions. Stat > Basic Statistics > 2 Proportions
2K Factorial DOE Performs a 2K Factorial DOE for full, fractional, or Plackett-Burman designs. Stat > DOE > Factorial > Analyze Factorial Design
2-Sample t Performs an independent 2-sample t-test and generates a confidence interval. Stat > Basic Statistics > 2-Sample t
Analysis Capture Use for analyses that do not have their own analysis capture tool. n/a
Attribute Agreement Analysis Assesses the agreement of nominal or ordinal ratings given by multiple appraisers. Stat > Quality Tools > Attribute Agreement Analysis
Best Subsets Regression Identifies the best-fitting regression models that can be constructed with the predictor variables you specify. Stat > Regression > Best Subsets
Binary Logistic Regression Performs logistic regression on a binary response variable. Stat > Regression > Binary Logistic Regression
Boxplot Assesses and compares sample distributions. Graph > Boxplot
C Chart Tracks the number of defects and detects the presence of special causes. Stat > Control Charts > Attributes Charts > C
Capability Analysis (Binomial) Produces a process capability report when your data are from a binomial distribution. Stat > Quality Tools > Capability Analysis > Binomial
Capability Analysis (Nonnormal) Produces a process capability report when your data do not follow a normal distribution or are transformed (using Johnson distribution system) to follow a normal distribution. Stat > Quality Tools > Capability Analysis > Nonnormal
Capability Analysis (Normal) Produces a process capability report when your data are from a normal distribution or are transformed to follow normal distribution using Box-Cox transformation. Stat > Quality Tools > Capability Analysis > Normal
Capability Analysis (Poisson) Produces a process capability report when your data are from a Poisson distribution. Stat > Quality Tools > Capability Analysis > Poisson
Capability Sixpack (Nonnormal) Produces a process capability report when your data do not follow a normal distribution. Stat > Quality Tools > Capability Sixpack > Nonnormal
Capability Sixpack (Normal) Produces a process capability report when your data follow a normal distribution. Stat > Quality Tools > Capability Sixpack > Normal
Chi-Square Goodness of Fit Tests whether your data follow a multinomial distribution with certain proportions. Stat > Tables > Chi-Square Goodness of Fit Test (One Variable)
Chi-Square Test of Independence Tests for dependence among characteristics in a two-way classification. Stat > Tables > Chi-Square Test (Two Way Table in Worksheet)
Contour Plot Maps measurement values as a function of two other variables.

Stat > DOE > Factorial

Stat > DOE > Response Surface

Stat > DOE > Mixture

Stat > DOE > Contour/Surface Plots

Graph > Contour Plot

Correlation Calculates the Pearson product moment correlation coefficient between each pair of variables you list. Stat > Basic Statistics > Correlation
Deviation From Nominal Chart Is a modification of either the I-MR or the Xbar-R/S Chart. It is used for low volume conditions where a family of parts shares the same process.

Stat > Control Charts > Variables Charts for Individuals > I-MR

Stat > Control Charts > Variables Charts for Subgroups > Xbar-R

Dotplot Assesses and compares distributions by plotting the values along a number line. Graph > Dotplot
Equal Variances Test Performs hypothesis tests for equality or homogeneity of variance. Stat > ANOVA > Test for Equal Variances
Fitted Line Plot Performs regression with linear and polynomial (second or third order) terms, if requested, of a single predictor variable and plots a regression line through the data. Stat > Regression > Fitted Line Plot
Gage Linearity & Bias Study Examines gage linearity and accuracy. Stat > Quality Tools > Gage Study > Gage Linearity and Bias Study
Gage R&R Study (Crossed) Determines how much of your observed process variation is due to measurement system variation when each part is measured multiple times by each operator. Stat > Quality Tools > Gage Study > Gage R&R Study (Crossed)
Gage R&R Study (Nested) Determines how much of your observed process variation is due to measurement system variation when each part is measured by only one operator. Stat > Quality Tools > Gage Study > Gage R&R Study (Nested)
Gage Run Chart Plots all of your observations by operator and part number. Stat > Quality Tools > Gage Study > Gage Run Chart
General Full Factorial (GFF) DOE Provides a cost-effective methodology for conducting controlled experiments (DOEs) where the factors (process inputs) can be held at any number of levels (settings). Stat > DOE > Factorial > Analyze Factorial Design
Graphical Summary Produces a graphical summary of your data. Stat > Basic Statistics > Graphical Summary
Graphing Y vs Categorical X Evaluates how process inputs affect static or dynamic patterns of the process output.

Graph > Histogram

Graph > Boxplot

Graph > Individual Value Plot

Graph > Time Series Plot

Stat > Control Charts > Variables Charts for Individuals > I-MR

Histogram Examines the shape and spread of sample data. Graph > Histogram
I-MR Chart Produces an Individuals chart and Moving Range chart in the same graph window. Stat > Control Charts > Variables Charts for Individuals > I-MR
Individual Value Plot Assesses and compares sample distributions by plotting individual values for each variable or group in a vertical column, making it easy to spot outliers and see the distribution shape. Graph > Individual Value Plot
Interactions Plot Plots means for each level of a factor with the level of a second factor held constant. Stat > ANOVA > Interactions Plot
Kruskal-Wallis Performs a hypothesis test of the equality of population medians for a one-way design (two or more populations). Stat > Nonparametrics > Kruskal-Wallis
Main Effects Plot Plots data means when you have multiple factors. Stat > ANOVA > Main Effects Plot
Mann-Whitney Performs a hypothesis test of the equality of two population medians and calculates the corresponding point estimate and confidence interval. Stat > Nonparametrics > Mann-Whitney
Matrix Plot Assesses the relationships between many pairs of variables at once by creating an array of scatterplots. Graph > Matrix Plot
Mixture DOE Analyzes a designed experiment in which the product under investigation is made up of several components or ingredients. Stat > DOE > Mixture > Analyze Mixture Design
Moods Median Test Performs a hypothesis test of the equality of two population medians and, like the Kruskal-Wallis Test, provides an nonparametric alternative to the one-way analysis of variance. Stat > Nonparametrics > Mood's Median Test
Multi-Vari Chart Presents analysis of variance data in a graphical form providing a "visual" alternative to analysis of variance. Stat > Quality Tools > Multi-Vari Chart
Multiple Regression Describes the statistical relationship between a response and two or more predictors. Stat > Regression > Regression
Multiple Response Optimization Determines the optimal conditions that will produce the "best" value for the response in a designed experiment.

Stat > DOE > Factorial

Stat > DOE > Response Surface

Stat > DOE > Mixture

Stat > DOE > Response Optimizer

Normality Test Generates a normal probability plot and performs a hypothesis test to examine whether or not the observations follow a normal distribution. Stat > Basic Statistics > Normality Test
NP Chart Tracks the number of defectives and detects the presence of special causes. Stat > Control Charts > Attributes Charts > NP
One-Way ANOVA Tests the equality of population means when classification is by one variable.

Stat > ANOVA > One-Way

Stat > ANOVA > One-Way (Unstacked)

P Chart Tracks the proportion defective and detects the presence of special causes. Stat > Control Charts > Attributes Charts > P
Paired t Tests the mean difference between paired observations when the paired differences follow a normal distribution. Stat > Basic Statistics > Paired t
Pareto Chart Is a type of bar chart in which the horizontal axis represents categories of interest, rather than a continuous scale. Stat > Quality Tools > Pareto Chart
Probability Plot Determines whether a particular distribution fits your data or compares different sample distributions. Graph > Probability Plot
Response Surface DOE Examines the relationship between one or more response variables and a set of quantitative experimental variables or factors. Stat > DOE > Response Surface > Analyze Response Surface Design
Run Chart Looks for evidence of patterns in your process data, and performs two tests for non-random behavior. Stat > Quality Tools > Run Chart
Scatterplot Illustrates the relationship between two variables by plotting one against the other. Graph > Scatterplot
Simple Regression Describes the statistical relationship between a response and one predictor. Stat > Regression > Regression
Six Sigma Process Report Produces six process capability reports for a single quality characteristic of a product. Six Sigma > Process Report (available only with the Six Sigma module)
Six Sigma Product Report Generates various benchmark statistics for the product. This report combines measures (defect counts, number of units, and number of opportunities) from many characteristics into a product capability, or measures from many products into a "business capability." Six Sigma > Product Report (available only with the Six Sigma module)
Stepwise Regression Removes and adds variables to the regression model for the purpose of identifying a useful subset of the predictors. Stat > Regression > Stepwise
Surface Plot Evaluates relationships between three variables at once.

Stat > DOE > Factorial

Stat > DOE > Response Surface

Stat > DOE > Mixture

Stat > DOE > Contour/Surface Plots

Graph > 3D Surface Plot

Time Series Plot Evaluates the time-based behavior of process inputs and outputs. Stat > Time Series > Times Series Plot
U Chart Tracks the number of defects per unit sampled and detects the presence of special causes. Stat > Control Charts > Attributes Charts > U
Xbar-R or S Chart Displays a control chart for subgroup means (Xbar chart) and a control chart for subgroup ranges (R chart) or subgroup standard deviations (S chart) in the same graph window.

Stat > Control Charts > Variables Charts for Subgroups > Xbar-R

Stat > Control Charts > Variables Charts for Subgroups > Xbar-S

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