Boxplot
Excel does not have a native BOXPLOT function, but you can replicate the function by following the instructions in the related links.
Go into your data to determine which values are outliers and if they're significant and random (not an apparent group), eliminate them. This will take them out of your boxplot.
When John Tukey invented the boxplot he suggested (somewhat arbitrarily) that any data points more than 1.5 times the length of the box (ie, the distance between the upper and lower quartiles) from the nearest end of the box should be regarded as outliers.For example, suppose the box length were 2, that the lower quartile were 5 and that the smallest data point were 1.1.5 * 2 = 35 - 3 = 21 < 2; in other words, this data point is too far away from the box.Hence, the smallest data point is an outlier.
A box and whisker plot is used to show range, you must first find out the quartiles. The first quartile is the left edge of the box, the third quartile is the right edge of the box and the median is the line in the middle. The whiskers are the highest and lowest values in your data set. Sometimes if you have a value in your data that is a long way out then you may not use it as a whisker, this is an outlier.A boxplot is a way of depicting groups of numerical data. They have many lines extending vertically from the whiskers (boxes).
Boxplot
A boxplot.
Excel does not have a native BOXPLOT function, but you can replicate the function by following the instructions in the related links.
A box plot is usually used to help graph minimum, first quarter, second quarter (mean), third quarter, max.
A box plot is usually used to help graph minimum, first quarter, second quarter (mean), third quarter, max.
Go into your data to determine which values are outliers and if they're significant and random (not an apparent group), eliminate them. This will take them out of your boxplot.
In descriptive statistics, a boxplot (also known as a box-and-whisker diagram or plot or candlestick chart) is a convenient way of graphically depicting groups of numerical data through their five-number summaries (the smallest observation, lower quartile (Q1), median, upper quartile (Q3), and largest observation). A boxplot also indicates which observations, if any, might be considered outliers. The boxplot was invented in 1977 by the American statistician John Tukey. Boxplots are able to visually show different types of populations, without making any assumptions of the underlying statistical distribution. The spacings between the different parts of the box help indicate variance, skewness and identify outliers. Boxplots can be drawn either horizontally or vertically.
to simply organise your numbers.ajm If you can make a histogram, a dotplot, or even a boxplot; there is no reason to do a steam and leaf plot. It's the worst graph. With a stem and leaf graph, you can see the distribution of data points, and determine whether it's normal distribution or not. As mentioned above, there are better graphs for doing that, though.
It is not possible to determine the range since there is always the possibility that there are outliers. Also, there is no information about the skewness of the data. If the distribution is symmetric, there is a high probability (99.75%) that the values will lie within 3 standard deviations of the mean - that is between 40 and 160.
bisect binary boxplot (box and whisker plot) binomial beta base
When John Tukey invented the boxplot he suggested (somewhat arbitrarily) that any data points more than 1.5 times the length of the box (ie, the distance between the upper and lower quartiles) from the nearest end of the box should be regarded as outliers.For example, suppose the box length were 2, that the lower quartile were 5 and that the smallest data point were 1.1.5 * 2 = 35 - 3 = 21 < 2; in other words, this data point is too far away from the box.Hence, the smallest data point is an outlier.
The median is Q2, if it is on the right side of the box, then then it is close to Q3 than it is to Q1. If the right line ( whisker) is longer than the left, it mean the biggest outlier is farther from Q3 than the smallest outlier is from Q1. All of this means the population from which the data was sampled was skewed to the right.