Matlab boxplot adjacent values












1














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'});









share|improve this question





























    1














    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'});









    share|improve this question



























      1












      1








      1







      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'});









      share|improve this question















      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






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      edited Nov 22 '18 at 9:42

























      asked Nov 20 '18 at 12:51









      Lukas W.

      166




      166
























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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.






          share|improve this answer





















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            1














            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.






            share|improve this answer


























              1














              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.






              share|improve this answer
























                1












                1








                1






                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.






                share|improve this answer












                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.







                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered Nov 21 '18 at 12:50









                Lukas W.

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