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In the above example, QI Macros tells you to "Reject the Null Hypothesis," because p < 0.05 (Means are Different/Means are not the Same). Interprets the Results for You: QI Macros compares the p value to alpha and tells you what that means. What's Cool about QI Macros Statistical Add-in for Excel? Note: TInv means "T Inverse" and is used in calculating the upper and lower confidence intervals. To test the variance, put the standard deviation (Stdev) test value in cell E6. You can also change the test mean and the calculations with change. 05 we "Reject the Null Hypothesis" (Means are Different/Means are not the Same). QI Macros will perform the calculations and interpret the results for you: QI Macros will prompt for a confidence level (default = 0.95)Īnd a Test Mean (light bulb life is less than or equal to 2,500 hours).Next, click on the QI Macros Menu > Statistical Tools > F & t Tests, and then select "t-Test: one sample":.Click and drag over the data to select it.Take your sample and input the data in Excel. Let's say you want to know if the life of a light bulb is greater than 2,500 hours. To conduct a t-Test using QI Macros follow these steps: QI Macros adds a new tab to Excel's menu. Note: Excel does NOT do one-sample t-tests QI Macros adds this functionality. Free Agile Lean Six Sigma Trainer Training.Animated Lean Six Sigma Video Tutorials.In this video, we’ll use a Mann-Whitney U-test to see if the distribution of weights of female and male mosquitoes are significantly different. H A: The population distributions in the two groups are not the same. H o: The population distributions in the two groups are the same. Note: This test does not test specifically if the mean or median of two groups are equal, only if the overall distributions are significantly different or not. The test statistic, U (or W), is a measure of the difference in rank sums. If the values in one group are generally higher than in the other, the rank sums will differ. This test is run by ranking all observations and then finding the sum of the ranks in each group.
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This test is an alternative to the two-sample independent t-test when the data fails the normality assumption or if the sample sizes in each group are too small to assess normality. A Mann-Whitney U-test (also called the rank-sum test, or Wilcoxin-Mann-Whitney test) uses sample data to test if a numeric outcome variable with any distribution differs across two independent groups.
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