Posts by Lean Sigma Corporation
Mann Whitney Testing with JMP
What is Mann Whitney Testing with JMP? Mann Whitney testing with JMP (also called Mann–Whitney U test or Wilcoxon rank-sum test) is a statistical hypothesis test to compare the medians of two populations that are not normally distributed. In a non-normal distribution, the median is the better representation of the center of the distribution. Null…
Read MoreOne Way ANOVA with JMP
What is One Way ANOVA? One way ANOVA is a statistical method to compare means of two or more populations. Null Hypothesis(H0):): μ1 = μ2 …= μk Alternative Hypothesis(Ha): At least one μi is different, where i is any value from 1 to k It is a generalized form of the two sample t-test since…
Read MoreTwo Sample Proportion Test with SigmaXL
What is the Two Sample Proportion Test with SigmaXL? The two sample proportion test with SigmaXL is a hypothesis test to compare the proportions of one certain event occurring in two populations following the binomial distribution. Null Hypothesis(H0): p1 = p2 Alternative Hypothesis(Ha): p1 ≠ p2 Two Sample Proportion Test Assumptions The sample data drawn…
Read MoreTwo Sample Proportion Test with JMP
What is the Two Sample Proportion Test? The two sample proportion test is a hypothesis test to compare the proportions of one certain event occurring in two populations following the binomial distribution. Null Hypothesis(H0): p1 = p2 Alternative Hypothesis(Ha): p1 ≠ p2 Two Sample Proportion Test Assumptions The sample data drawn from the populations of…
Read MorePaired t Test with JMP
What is the Paired t Test? A Third type of Two Sample t-Test is the Paired t Test. This test is used when the two populations are dependent of each other, so each data point from one distribution corresponds to a data point in the other distribution. When using a paired t test, the test…
Read MoreTwo Sample t Test with JMP
What is Two Sample t Test? Two sample t test is a hypothesis test to study whether there is a statistically significant difference between the means of two populations. Null Hypothesis (H0): μ1 = μ2 Alternative Hypothesis Ha) : μ1 ≠ μ2 Where: μ1 is the mean of one population and μ2 is the mean of…
Read MoreOne Sample Proportion Test with SigmaXL
What is the One Sample Proportion Test with SigmaXL? One sample proportion test with SigmaXL is a hypothesis test to compare the proportion of one certain outcome (e.g. the number of successes per the number of trials, or the number of defects per the total number of opportunities) occurring in a population following the binomial…
Read MoreOne Sample Proportion Test with JMP
What is the One Sample Proportion Test? One sample proportion test is a hypothesis test to compare the proportion of one certain outcome (e.g. the number of successes per the number of trials, or the number of defects per the total number of opportunities) occurring in a population following the binomial distribution with a specified…
Read MoreOne Sample Wilcoxon Test with JMP
What is the One Sample Wilcoxon Test? The one sample Wilcoxon test is a hypothesis test to compare the median of one population with a specified value. Null Hypothesis (H0): η = η0 Alternative Hypothesis (Ha): η ≠ η0 It is an alternative test of one sample t-test when the data distribution is non-normal. It is more powerful…
Read MoreOne Sample Wilcoxon Test with SigmaXl
What is the One Sample Wilcoxon Test with SigmaXL? The one sample Wilcoxon test with SigmaXL is a hypothesis test to compare the median of one population with a specified value. Null Hypothesis (H0): η = η0 Alternative Hypothesis (Ha): η ≠ η0 It is an alternative test of one sample t-test when the distribution of the…
Read MoreKruskal 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.…
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