Posts Tagged ‘How To’
Kruskal Wallis Test with SigmaXL
What is a Kruskal Wallis Test with SigmaXL The Kruskal Wallis test with SigmaXL is a statistical hypothesis used test to compare the medians among more than two groups. Null Hypothesis (H0): η1 = η2 = … = ηk Alternative Hypothesis (Ha): at least one of the medians is different from others.Where: ηi is the…
Read MoreOne Sample t Test with JMP
One Sample t Test What is a t Test? In statistics, a t test is a hypothesis test in which the test statistic follows a Student’s t distribution if the null hypothesis is true. We apply a one sample t test when the population variance (σ) is unknown and we use the sample standard deviation…
Read MoreKruskal Wallis Test with JMP
What is Kruskal–Wallis One-Way Analysis of Variance? The Kruskal Wallis one-way analysis of variance is a statistical hypothesis test to compare the medians among more than two groups. Null Hypothesis (H0): η1 = η2 = … = ηk Alternative Hypothesis (Ha): at least one of the medians is different from others. Where: ni is the…
Read MoreP Chart with SigmaXL
What is a P Chart? The P chart plots the percentage of defectives in one subgroup as a data point. It considers the situation when the subgroup size of inspected units is not constant. The underlying distribution of the P-chart is binomial distribution. Use SigmaXL to Plot a P Chart Data File: “P” tab in…
Read MoreP Chart with Minitab
What is a P Chart? The P chart plots the percentage of defectives in one subgroup as a data point. It considers the situation when the subgroup size of inspected units is not constant. The underlying distribution of the P-chart is binomial distribution. Use Minitab to Plot a P Chart Data File: “P” tab in…
Read MoreP Chart with JMP
What is a P Chart? The P chart plots the percentage of defectives in one subgroup as a data point. It considers the situation when the subgroup size of inspected units is not constant. The underlying distribution of the P-chart is binomial distribution. P Chart Equations Data Point: Center Line: Control Limits: …
Read MoreU Chart with SigmaXL
What is a U Chart with SigmaXL? The U chart with SigmaXL is a type of control chart used to monitor discrete (count) data where the sample size is greater than one, typically the average number of defects per unit. Defect vs. Defective Remember the difference between defect and defective? A defect of a unit…
Read MoreU Chart with JMP
What is a U Chart? The U chart is a type of control chart used to monitor discrete (count) data where the sample size is greater than one, typically the average number of defects per unit. Defect vs. Defective Remember the difference between defect and defective? A defect of a unit is the unit’s characteristic…
Read MoreU Chart with Minitab
What is a U Chart? The U chart is a type of control chart used to monitor discrete (count) data where the sample size is greater than one, typically the average number of defects per unit. Defect vs. Defective Remember the difference between defect and defective? A defect of a unit is the unit’s characteristic…
Read MoreXbar R Charts with JMP
Xbar R Chart The Xbar R chart is a control chart for continuous data with a constant subgroup size between two and ten. The Xbar chart plots the average of a subgroup as a data point. The R chart plots the difference between the highest and lowest values within a subgroup as a data point.…
Read MoreXbar R Charts with SigmaXL
What is an Xbar R Chart with SigmaXL? The Xbar R chart with SigmaXL is a control chart for continuous data with a constant subgroup size between two and ten. The Xbar chart plots the average of a subgroup as a data point. The R chart plots the difference between the highest and lowest values…
Read MoreXbar R Charts with Minitab
Xbar R Chart The Xbar R chart is a control chart for continuous data with a constant subgroup size between two and ten. The Xbar chart plots the average of a subgroup as a data point. The R chart plots the difference between the highest and lowest values within a subgroup as a data point.…
Read MoreIR Chart with Minitab
What is an 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…
Read MoreIR 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 MoreIR 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 MoreFractional 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 MoreFractional 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 MoreFractional 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 MoreFull 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 MoreFull 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…
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