I made up this story: In a company there have been head injuries, so they brought in a medical student to investigate/research. The researcher gathered all employees blood pressure, gender, age, and eye sight data. The result was that mostly men were affected, with all other factors being what you would expect given the employees. The company was forced by the insurance company to make helmets mandatory for all men due to their gender being a risk factor. Because the engineers were all men they were over proportionally affected and did not like to wear the helmets, so they got together and demanded further research into what caused the injuries and how to remove the cause. This time the secretary was tasked with the follow up because she knew Excel. She took her mail scale and measuring tape and went around asking everyone if they drank coffee or tea, measured the weight of the content of people’s pockets and how high they were with and without shoes. To be thorough she did this for every week day separately. After importing the previous data, she found many correlations between attributes and other attributes variances but what stood out were the correlations between injuries to Friday, pocket weight, gender, height with shoes in ascending order. A histogram of injuries per “height without shoes”-class showed a sharp increase at 6 feet. Being taller than 6′ was clearly the cause. After having presented her findings, one woman stood up and remarked: “But I am not 6′, and it happened to me!” Counting the women taller than 6′ the secretary found none. --- I could go on but I think you get it and we can save us the time. After more searching they found that their 6 foot door frames were the best thing to change and that some women had been wearing higher shoes on Fridays. My point is that gender was not the cause and especially “too low doors” AND (“over 6′ tall” OR (“tall for a woman” AND “high shoes”)) was the problem. Neither being a tall woman nor high shoes alone would have been causal in this scenario. I would have loved to include wheel chairs in this but found it too complicated.
I made up this story:
In a company there have been head injuries, so they brought in a medical student to investigate/research.
The researcher gathered all employees blood pressure, gender, age, and eye sight data.
The result was that mostly men were affected, with all other factors being what you would expect given the employees.
The company was forced by the insurance company to make helmets mandatory for all men due to their gender being a risk factor.
Because the engineers were all men they were over proportionally affected and did not like to wear the helmets, so they got together and demanded further research into what caused the injuries and how to remove the cause.
This time the secretary was tasked with the follow up because she knew Excel. She took her mail scale and measuring tape and went around asking everyone if they drank coffee or tea, measured the weight of the content of people’s pockets and how high they were with and without shoes. To be thorough she did this for every week day separately.
After importing the previous data, she found many correlations between attributes and other attributes variances but what stood out were the correlations between injuries to Friday, pocket weight, gender, height with shoes in ascending order. A histogram of injuries per “height without shoes”-class showed a sharp increase at 6 feet. Being taller than 6′ was clearly the cause.
After having presented her findings, one woman stood up and remarked: “But I am not 6′, and it happened to me!” Counting the women taller than 6′ the secretary found none.
---
I could go on but I think you get it and we can save us the time. After more searching they found that their 6 foot door frames were the best thing to change and that some women had been wearing higher shoes on Fridays.
My point is that gender was not the cause and especially “too low doors” AND (“over 6′ tall” OR (“tall for a woman” AND “high shoes”)) was the problem. Neither being a tall woman nor high shoes alone would have been causal in this scenario.
I would have loved to include wheel chairs in this but found it too complicated.