IR Chart with SigmaXL

What is an IR Chart with SigmaXL? The IR chart with SigmaXL (also called individual-moving range chart or I-MR chart) is a popular control chart for continuous data with subgroup size equal to one. The I chart plots an individual observation as a data point. The MR chart plots the absolute value of the difference…

Read More

IR Chart with JMP

IR Chart The IR chart (also called individual-moving range chart or I-MR chart) is a popular control chart for continuous data with subgroup size equal to one. The I chart plots an individual observation as a data point. The MR chart plots the absolute value of the difference between two consecutive observations in individual charts…

Read More

Fractional Factorial Designs with JMP

What Are Fractional Factorial Experiments? In simple terms, a fractional factorial experiment is a subset of a full factorial experiment. Fractional factorials use fewer treatment combinations and runs Fractional factorials are less able to determine effects because of fewer degrees of freedom available to evaluate higher order interactions Fractional factorials can be used to screen…

Read More

Fractional Factorial Designs with SigmaXL

What Are Fractional Factorial Designs with SigmaXL? In simple terms, a fractional factorial design with SigmaXL is a subset of a full factorial experiment. Fractional factorials use fewer treatment combinations and runs. Fractional factorials are less able to determine effects because of fewer degrees of freedom available to evaluate higher order interactions. Fractional factorials can…

Read More

Fractional Factorial Designs with Minitab

What Are Fractional Factorial Experiments? In simple terms, a fractional factorial experiment is a subset of a full factorial experiment. Fractional factorials use fewer treatment combinations and runs. Fractional factorials are less able to determine effects because of fewer degrees of freedom available to evaluate higher order interactions. Fractional factorials can be used to screen…

Read More

Full Factorial DOE with JMP

Full Factorial DOE In a full factorial experiment, all of the possible combinations of factors and levels are created and tested. For example, for two-level design (i.e.each factor has two levels) with k factors, there are 2k possible scenarios or treatments. Two factors, each with two levels, we have 22 = 4 treatments Three factors, each…

Read More

Full Factorial DOE with Minitab

What is a Full Factorial DOE? In a full factorial experiment, all of the possible combinations of factors and levels are created and tested. For example, for two-level design (i.e.each factor has two levels) with k factors, there are 2k possible scenarios or treatments. Two factors, each with two levels, we have 22 = 4 treatments…

Read More

Full Factorial DOE with SigmaXL

What is a Full Factorial DOE with SigmaXL? In a Full Factorial DOE with SigmaXL, all of the possible combinations of factors and levels are created and tested. For example, for two-level design (i.e.each factor has two levels) with k factors, there are 2k possible scenarios or treatments. Two factors, each with two levels, we…

Read More

Logistic Regression with SigmaXL

What is Logistic Regression with SigmaXL? The Logistic Regression with SigmaXL is a statistical method to predict the probability of an event occurring by fitting the data to a logistic curve using logistic function. The regression analysis used for predicting the outcome of a categorical dependent variable, based on one or more predictor variables. The…

Read More

Chi Square Test with JMP

Chi Square (Contingency Tables) We have looked at hypothesis tests to analyze the proportion of one population vs. a specified value, and the proportions of two populations, but what do we do if we want to analyze more than two populations? A chi-square test is a hypothesis test in which the sampling distribution of the…

Read More

Chi Square Test with Minitab

Chi Square (Contingency Tables) We have looked at hypothesis tests to analyze the proportion of one population vs. a specified value, and the proportions of two populations, but what do we do if we want to analyze more than two populations? A chi-square test is a hypothesis test in which the sampling distribution of the…

Read More

Attribute MSA with SigmaXL

Implement an Attribute MSA with SigmaXL Data File: “Attribute MSA” tab in “Sample Data.xlsx” (an example in the AIAG MSA Reference Manual, 3rd Edition). Step 1: Reorganize the original data into four new columns (i.e., Appraiser, Assessed Result, Part, and Reference). Select the entire range of the original data (“Part”, “Reference”, “Appraiser A”, “Appraiser B”…

Read More

Attribute MSA with JMP

Use JMP to Implement an Attribute MSA This article discusses using an Attribute MSA with JMP. It’s important to know because whenever something is measured repeatedly or by different people or processes, the results of the measurements will vary. Variation comes from two primary sources: Differences between the parts being measured The measurement system We…

Read More

Run Chart with Minitab

Why we use a Run Chart A run chart is a chart used to present data in time order. These charts capture process performance over time. The X axis indicates time and the Y axis shows the observed values. A run chart is similar to a scatter plot in that it shows the relationship between X and…

Read More

Moods Median Test with JMP

What is Moods Median Test? Mood’s median test is a statistical test to compare the medians of two or more populations. Null Hypothesis (H0): η1 = … = ηk Alternative Hypothesis (Ha): At least one of the medians is different from the others The symbol k is the number of groups of our interest and…

Read More

Chi Square Test with SigmaXL

Chi Square Test with SigmaXL (Contingency Tables) We have looked at hypothesis tests to analyze the proportion of one population vs. a specified value, and the proportions of two populations, but what do we do if we want to analyze more than two populations? A chi-square test with SigmaXL is a hypothesis test in which…

Read More

Logistic Regression with Minitab

What is Logistic Regression? Logistic regression is a statistical method to predict the probability of an event occurring by fitting the data to a logistic curve using logistic function. The regression analysis used for predicting the outcome of a categorical dependent variable, based on one or more predictor variables. The logistic function used to model…

Read More

Logistic Regression with JMP

What is Logistic Regression? Logistic regression is a statistical method to predict the probability of an event occurring by fitting the data to a logistic curve using logistic function. The regression analysis used for predicting the outcome of a categorical dependent variable, based on one or more predictor variables. The logistic function used to model…

Read More

Stepwise Regression with JMP

What is Stepwise Regression? Stepwise regression is a statistical method to automatically select regression models with the best sets of predictive variables from a large set of potential variables. There are different statistical methods used in stepwise regression to evaluate the potential variables in the model: F-test T-test R-square AIC Three Approaches to Stepwise Regression…

Read More

Stepwise Regression with Minitab

What is Stepwise Regression? Stepwise regression is a statistical method to automatically select regression models with the best sets of predictive variables from a large set of potential variables. There are different statistical methods used in stepwise regression to evaluate the potential variables in the model: F-test T-test R-square AIC Three Approaches to Stepwise Regression…

Read More