Posts Tagged ‘JMP’
EWMA Chart with JMP
What is EWMA Chart? The EWMA chart (Exponentially-Weighted Moving Average Chart) is a control chart monitoring the exponentially-weighted average of previous and present subgroup means. The more recent data get more weight than older data. It detects the shift of the process mean from the process target over time. The underlying distribution of the EWMA…
Read MoreCumSum Chart with JMP
What is a CumSum Chart? The CumSum chart (also called cumulative sum control chart or CUMSUM chart) is a control chart of monitoring the cumulative sum of the subgroup mean deviations from the process target. It detects the shift of the process mean from the process target over time. The underlying distribution of the CumSum…
Read MoreCreating an NP Chart with JMP
Creating an NP Chart with JMP What is NP Chart with JMP? The NP chart with JMP is a control chart monitoring the count of defectives using JMP statistical software to produce the results. It plots the number of defectives in one subgroup as a data point. The subgroup size of the NP chart is…
Read MoreXbar S Chart with JMP
What is a Xbar S Chart? The X-S chart (also called Xbar S chart) is a control chart for continuous data with a constant subgroup size greater than ten. The Xbar chart plots the average of a subgroup as a data point. The S chart plots the standard deviation within a subgroup as a data…
Read MoreMann 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 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 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 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 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 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 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 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 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 MoreChi 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…
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