Matlab boxplot adjacent values
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I found that calculating an index to specify outliers of a dataset according to how the boxplot works does not give the same results. Please find below an example where I create some data, extract the values from the boxplot (as seen in datatips in the figure window) and compare them to the values I calculated.
While the median and quartiles match up the upper and lower adjacent values do not. According to the Matlab help under 'Whisker', the adjacent values are calculated as q3 + w*(q3-q1) where q3 and q1 are the quantiles and w is the specified whisker length.
Am I calculating this wrong or is there any other mistake? I would like to be able to explain the error.
Screenshot of results table (please note the results vary due to random data)
%Boxplot test
% create random, normally distributed dataset
data = round(randn(1000,1)*10,2);
figure(10)
clf
boxplot(data,'Whisker',1.5)
clear stats tmp
% read data from boxplot, same values as can be seen in datatips in the figure window
h = findobj(gcf,'tag','Median');
tmp = get(h,'YData');
stats(1,1) = tmp(1);
h = findobj(gcf,'tag','Box');
tmp = get(h,'YData');
stats(1,2) = tmp(1);
stats(1,3) = tmp(2);
h = findobj(gcf,'tag','Upper Adjacent Value');
tmp = get(h,'YData');
stats(1,4) = tmp(1);
h = findobj(gcf,'tag','Lower Adjacent Value');
tmp = get(h,'YData');
stats(1,5) = tmp(1);
% calculated data
stats(2,1) = median(data);
stats(2,2) = quantile(data,0.25);
stats(2,3) = quantile(data,0.75);
range = stats(2,3) - stats(2,2);
stats(2,4) = stats(2,3) + 1.5*range;
stats(2,5) = stats(2,2) - 1.5*range;
% error calculation
for k=1:size(stats,2)
stats(3,k) = stats(2,k)-stats(1,k);
end %for k
% convert results to table with labels
T = array2table(stats,'VariableNames',{'Median','P25','P75','Upper','Lower'}, ...
'RowNames',{'Boxplot','Calculation','Error'});
matlab statistics boxplot
asked Nov 20 at 12:51
Lukas W.
166
add a comment |
up vote
1
down vote
favorite
I found that calculating an index to specify outliers of a dataset according to how the boxplot works does not give the same results. Please find below an example where I create some data, extract the values from the boxplot (as seen in datatips in the figure window) and compare them to the values I calculated.
While the median and quartiles match up the upper and lower adjacent values do not. According to the Matlab help under 'Whisker', the adjacent values are calculated as q3 + w*(q3-q1) where q3 and q1 are the quantiles and w is the specified whisker length.
Am I calculating this wrong or is there any other mistake? I would like to be able to explain the error.
Screenshot of results table (please note the results vary due to random data)
%Boxplot test
% create random, normally distributed dataset
data = round(randn(1000,1)*10,2);
figure(10)
clf
boxplot(data,'Whisker',1.5)
clear stats tmp
% read data from boxplot, same values as can be seen in datatips in the figure window
h = findobj(gcf,'tag','Median');
tmp = get(h,'YData');
stats(1,1) = tmp(1);
h = findobj(gcf,'tag','Box');
tmp = get(h,'YData');
stats(1,2) = tmp(1);
stats(1,3) = tmp(2);
h = findobj(gcf,'tag','Upper Adjacent Value');
tmp = get(h,'YData');
stats(1,4) = tmp(1);
h = findobj(gcf,'tag','Lower Adjacent Value');
tmp = get(h,'YData');
stats(1,5) = tmp(1);
% calculated data
stats(2,1) = median(data);
stats(2,2) = quantile(data,0.25);
stats(2,3) = quantile(data,0.75);
range = stats(2,3) - stats(2,2);
stats(2,4) = stats(2,3) + 1.5*range;
stats(2,5) = stats(2,2) - 1.5*range;
% error calculation
for k=1:size(stats,2)
stats(3,k) = stats(2,k)-stats(1,k);
end %for k
% convert results to table with labels
T = array2table(stats,'VariableNames',{'Median','P25','P75','Upper','Lower'}, ...
'RowNames',{'Boxplot','Calculation','Error'});
matlab statistics boxplot
asked Nov 20 at 12:51
Lukas W.
166
add a comment |
up vote
1
down vote
favorite
up vote
1
down vote
favorite
I found that calculating an index to specify outliers of a dataset according to how the boxplot works does not give the same results. Please find below an example where I create some data, extract the values from the boxplot (as seen in datatips in the figure window) and compare them to the values I calculated.
While the median and quartiles match up the upper and lower adjacent values do not. According to the Matlab help under 'Whisker', the adjacent values are calculated as q3 + w*(q3-q1) where q3 and q1 are the quantiles and w is the specified whisker length.
Am I calculating this wrong or is there any other mistake? I would like to be able to explain the error.
Screenshot of results table (please note the results vary due to random data)
%Boxplot test
% create random, normally distributed dataset
data = round(randn(1000,1)*10,2);
figure(10)
clf
boxplot(data,'Whisker',1.5)
clear stats tmp
% read data from boxplot, same values as can be seen in datatips in the figure window
h = findobj(gcf,'tag','Median');
tmp = get(h,'YData');
stats(1,1) = tmp(1);
h = findobj(gcf,'tag','Box');
tmp = get(h,'YData');
stats(1,2) = tmp(1);
stats(1,3) = tmp(2);
h = findobj(gcf,'tag','Upper Adjacent Value');
tmp = get(h,'YData');
stats(1,4) = tmp(1);
h = findobj(gcf,'tag','Lower Adjacent Value');
tmp = get(h,'YData');
stats(1,5) = tmp(1);
% calculated data
stats(2,1) = median(data);
stats(2,2) = quantile(data,0.25);
stats(2,3) = quantile(data,0.75);
range = stats(2,3) - stats(2,2);
stats(2,4) = stats(2,3) + 1.5*range;
stats(2,5) = stats(2,2) - 1.5*range;
% error calculation
for k=1:size(stats,2)
stats(3,k) = stats(2,k)-stats(1,k);
end %for k
% convert results to table with labels
T = array2table(stats,'VariableNames',{'Median','P25','P75','Upper','Lower'}, ...
'RowNames',{'Boxplot','Calculation','Error'});
matlab statistics boxplot
asked Nov 20 at 12:51
Lukas W.
166
I found that calculating an index to specify outliers of a dataset according to how the boxplot works does not give the same results. Please find below an example where I create some data, extract the values from the boxplot (as seen in datatips in the figure window) and compare them to the values I calculated.
While the median and quartiles match up the upper and lower adjacent values do not. According to the Matlab help under 'Whisker', the adjacent values are calculated as q3 + w*(q3-q1) where q3 and q1 are the quantiles and w is the specified whisker length.
Am I calculating this wrong or is there any other mistake? I would like to be able to explain the error.
Screenshot of results table (please note the results vary due to random data)
%Boxplot test
% create random, normally distributed dataset
data = round(randn(1000,1)*10,2);
figure(10)
clf
boxplot(data,'Whisker',1.5)
clear stats tmp
% read data from boxplot, same values as can be seen in datatips in the figure window
h = findobj(gcf,'tag','Median');
tmp = get(h,'YData');
stats(1,1) = tmp(1);
h = findobj(gcf,'tag','Box');
tmp = get(h,'YData');
stats(1,2) = tmp(1);
stats(1,3) = tmp(2);
h = findobj(gcf,'tag','Upper Adjacent Value');
tmp = get(h,'YData');
stats(1,4) = tmp(1);
h = findobj(gcf,'tag','Lower Adjacent Value');
tmp = get(h,'YData');
stats(1,5) = tmp(1);
% calculated data
stats(2,1) = median(data);
stats(2,2) = quantile(data,0.25);
stats(2,3) = quantile(data,0.75);
range = stats(2,3) - stats(2,2);
stats(2,4) = stats(2,3) + 1.5*range;
stats(2,5) = stats(2,2) - 1.5*range;
% error calculation
for k=1:size(stats,2)
stats(3,k) = stats(2,k)-stats(1,k);
end %for k
% convert results to table with labels
T = array2table(stats,'VariableNames',{'Median','P25','P75','Upper','Lower'}, ...
'RowNames',{'Boxplot','Calculation','Error'});
matlab statistics boxplot
matlab statistics boxplot
asked Nov 20 at 12:51
Lukas W.
166
asked Nov 20 at 12:51
Lukas W.
166
edited Nov 22 at 9:42
asked Nov 20 at 12:51
Lukas W.
166
asked Nov 20 at 12:51
Lukas W.
166
asked Nov 20 at 12:51
Lukas W.
166
166
add a comment |
add a comment |
1 Answer
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While the calculation of the boundaries, e.g. q3 = q3 + w*(q3-q1), is correct, it is not displayed in the boxplot. What is actually displayed and marked as upper/lower adjacent value is the minimum and maximum of the values within the aforementioned boundaries.
Regarding the initial task leading to the question: For applying the same filtering of outliers as in the boxplot the calculated boundaries can be used.
answered Nov 21 at 12:50
Lukas W.
166
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
1
down vote
accepted
While the calculation of the boundaries, e.g. q3 = q3 + w*(q3-q1), is correct, it is not displayed in the boxplot. What is actually displayed and marked as upper/lower adjacent value is the minimum and maximum of the values within the aforementioned boundaries.
Regarding the initial task leading to the question: For applying the same filtering of outliers as in the boxplot the calculated boundaries can be used.
answered Nov 21 at 12:50
Lukas W.
166
add a comment |
up vote
1
down vote
accepted
While the calculation of the boundaries, e.g. q3 = q3 + w*(q3-q1), is correct, it is not displayed in the boxplot. What is actually displayed and marked as upper/lower adjacent value is the minimum and maximum of the values within the aforementioned boundaries.
Regarding the initial task leading to the question: For applying the same filtering of outliers as in the boxplot the calculated boundaries can be used.
answered Nov 21 at 12:50
Lukas W.
166
add a comment |
up vote
1
down vote
accepted
up vote
1
down vote
accepted
While the calculation of the boundaries, e.g. q3 = q3 + w*(q3-q1), is correct, it is not displayed in the boxplot. What is actually displayed and marked as upper/lower adjacent value is the minimum and maximum of the values within the aforementioned boundaries.
Regarding the initial task leading to the question: For applying the same filtering of outliers as in the boxplot the calculated boundaries can be used.
answered Nov 21 at 12:50
Lukas W.
166
While the calculation of the boundaries, e.g. q3 = q3 + w*(q3-q1), is correct, it is not displayed in the boxplot. What is actually displayed and marked as upper/lower adjacent value is the minimum and maximum of the values within the aforementioned boundaries.
Regarding the initial task leading to the question: For applying the same filtering of outliers as in the boxplot the calculated boundaries can be used.
answered Nov 21 at 12:50
Lukas W.
166
answered Nov 21 at 12:50
Lukas W.
166
answered Nov 21 at 12:50
Lukas W.
166
answered Nov 21 at 12:50
Lukas W.
166
166
add a comment |
add a comment |
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