BOX PLOT WHISKERS MINITAB

Outliers Outliers, which are data values that are far away from other data values, can strongly affect your results. Center and spread Examine the following elements to learn more about the center and spread of your sample data. If you want to analyze severely skewed data, read the data considerations topic for the analysis to make sure that you can use data that are not normal. When data are skewed, the majority of the data are located on the high or low side of the graph. Outliers, which are data values that are far away from other data values, can strongly affect your results. In This Topic Step 1:

Skewness indicates that the data may not be normally distributed. If your data are skewed nonnormal , read the data considerations topic for the analysis to make sure that you can use data that are not normal. Sample size N The sample size can affect the appearance of the graph. The median thicknesses for some groups seem to be different. The median weights of the groups of cereal boxes are similar, but the weights of some groups are more variable than others. Complete the following steps to interpret a boxplot. Then, repeat the analysis.

“Ingrown” or “inverted” whiskers on a boxplot

Assess the key characteristics Examine the center and spread of the distribution. For more information on how to interpret the quartiles, go to What are quartiles? For example, a boxplot may show that the median length of wood boox is much lower than the target length of 8 feet. Often, outliers are easiest to identify on a boxplot. Examine the center and spread of the distribution.

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Spreads Look for differences between the spreads of the groups. If the sample size is too small, the quartiles and outliers shown by the boxplot may not be meaningful. The sample size can affect the appearance of the graph.

Most subjects have a resting heart rate that is between 64 and 80, but some subjects have heart rates that are as low as 48 and miitab high as When data are skewed, the majority of the data are located on the high or low side of the graph.

Overview for Boxplot – Minitab Express

Hold the pointer over the boxplot to display a tooltip that shows these statistics. Some analyses assume that your data come from a normal distribution. Outliers Outliers, which are data values that are far away from other data values, can strongly affect your results.

Median The median is represented by the line in the box. If the sample size is too small, the quartiles and outliers shown by the boxplot may not be meaningful. A few items fail immediately and many more items fail later. Outliers Outliers, which are data values that are far away from other data values, can strongly affect your results. The boxplot with right-skewed data shows wait times.

The median weights of the groups of cereal boxes are similar, but the weights of some groups are more variable than others. Investigate any surprising or undesirable characteristics on the boxplot.

For example, this boxplot shows the fill weights of cereal boxes from four production lines. Whiskers The whiskers extend from either side of the box.

Complete the following steps to interpret a boxplot. For example, the following boxplot shows the thickness of wire from four suppliers. Median The median is represented by the line in the box. Interpret the key results for Boxplot Learn more about Minitab To determine whether a difference in spread variance is statistically qhiskers, do one of the following: Assess and compare groups If your boxplot has groups, assess and compare the center and spread of groups.

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Sample size n The sample size can affect the appearance of the graph.

Interpret the key results for Boxplot – Minitab

For example, this boxplot shows the thickness of wire produced by four suppliers. Look for indicators of nonnormal or unusual data Step 3: Tip Hold the pointer over the outlier to identify the data point. Use a test for equal variances if you have three or more groups.

For example, although the following boxplots seem quite different, both of them were created using randomly selected samples of data from the same population. For specific information on how the quartiles are calculated, go to Methods and dhiskers for Graphical Summary. Hold the pointer over the boxplot to display a tooltip that shows these statistics.

Outliers, which are data values that are far away from other data values, can strongly affect your results. Centers Look for differences between the centers of the groups.