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The study variation is calculated as the standard deviation for each source of variation multiplied by 6 or the multiplier that you specify in Study variation.. Usually, process variation is defined as 6s, where s is the standard deviation as an estimate of the population standard deviation (denoted by σ or sigma).
Enter one or more grouping variables in By variables to create a separate scatterplot for each level of the grouping variables. The columns that you enter must be the same length as the columns in Y variables and X variables.The y-scales for each variable are the same across the multiple scatterplots.
Use a stem-and-leaf plot to display the actual data values in a binned format. Though similar to a dotplot, a stem-and-leaf plot is turned on its side.
The boxplot with right-skewed data shows wait times. Most of the wait times are relatively short, and only a few wait times are long. The boxplot with left-skewed data shows failure time data.
The scatterplot shows the actual response values on the x-axis and the fitted response values on the y-axis. The calculated line represents when the actual value and the response value are equal.
Interpretation. Use to compare the fits of different time series models. Smaller values indicate a better fit. If a single model does not have the lowest values for all 3 accuracy measures, MAPE is usually the preferred measurement.
Use Interval Plot to assess and compare confidence intervals of the means of groups. An interval plot shows a 95% confidence interval for the mean of each group. An interval plot works best when the sample size is at least 10 for each group. Usually, the larger the sample size, the smaller and more precise the confidence interval.
The lot quality units for a variables acceptance sampling plan are based on counts of defective items. Percent defective Represents the percentage defective as a value between 0 and 100.
Interpret the results. Interpret the Moving Range chart (MR chart) first to examine the process variation. None of the points are outside the control limits and the points display a random pattern.
Use Heatmap to investigate the relationship between one or more categorical variables and a summary statistic. The summary statistic that you select, such as mean or sum, determines the color gradient for each rectangle. The color gradient is the shade that Minitab colors the rectangles.