Finding a proper way to correlate categorical data when chi_square p value is zero











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To summarize the situation: imagine I have two groups of people – each group is given the same set of images. One group is given the task to assign the image to an animal from a list of animals with the goal of picking an animal from the list in which they believe the animal in the image is closest related too. The other group is given the task to accurately assign what animal is in each picture from another list of animals. The list of animals that both groups had access too are not identical. I made a table showing the count for where each picture landed given the two groups’ choices.



At first, I thought I could relate the two categorical variables via chi square, however when I calculate the p value via python’s chisquare_contigency function I get back a p value of zero, which is making me doubt what I am doing is right. I ran the python function on my table as is in picture. I have thought about trying a fisher’s test, but I am not entirely sure what I should be using. Thanks.
Table of Data










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    To summarize the situation: imagine I have two groups of people – each group is given the same set of images. One group is given the task to assign the image to an animal from a list of animals with the goal of picking an animal from the list in which they believe the animal in the image is closest related too. The other group is given the task to accurately assign what animal is in each picture from another list of animals. The list of animals that both groups had access too are not identical. I made a table showing the count for where each picture landed given the two groups’ choices.



    At first, I thought I could relate the two categorical variables via chi square, however when I calculate the p value via python’s chisquare_contigency function I get back a p value of zero, which is making me doubt what I am doing is right. I ran the python function on my table as is in picture. I have thought about trying a fisher’s test, but I am not entirely sure what I should be using. Thanks.
    Table of Data










    share|cite|improve this question
























      up vote
      0
      down vote

      favorite









      up vote
      0
      down vote

      favorite











      To summarize the situation: imagine I have two groups of people – each group is given the same set of images. One group is given the task to assign the image to an animal from a list of animals with the goal of picking an animal from the list in which they believe the animal in the image is closest related too. The other group is given the task to accurately assign what animal is in each picture from another list of animals. The list of animals that both groups had access too are not identical. I made a table showing the count for where each picture landed given the two groups’ choices.



      At first, I thought I could relate the two categorical variables via chi square, however when I calculate the p value via python’s chisquare_contigency function I get back a p value of zero, which is making me doubt what I am doing is right. I ran the python function on my table as is in picture. I have thought about trying a fisher’s test, but I am not entirely sure what I should be using. Thanks.
      Table of Data










      share|cite|improve this question













      To summarize the situation: imagine I have two groups of people – each group is given the same set of images. One group is given the task to assign the image to an animal from a list of animals with the goal of picking an animal from the list in which they believe the animal in the image is closest related too. The other group is given the task to accurately assign what animal is in each picture from another list of animals. The list of animals that both groups had access too are not identical. I made a table showing the count for where each picture landed given the two groups’ choices.



      At first, I thought I could relate the two categorical variables via chi square, however when I calculate the p value via python’s chisquare_contigency function I get back a p value of zero, which is making me doubt what I am doing is right. I ran the python function on my table as is in picture. I have thought about trying a fisher’s test, but I am not entirely sure what I should be using. Thanks.
      Table of Data







      probability random-variables python






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      asked Nov 25 at 21:52









      bbbeenn32

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