Research Methods

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A Type I error is a greater concern than a Type II error. Agree or disagree with this statement and use examples to support your position. Choose a classmate with an opposing view and try to respectfully persuade them to your point of view.

Please include the name of the person or question to which you are replying in the subject line. For example, "Tom's response to Susan's comment."

Friendly reminder to begin your Discussion Initial Post as early in the week as possible. Waiting till the end of the Unit sacrifices your learning, sharing and communication with one another. 

Kindly address the discussion question(s) submitting a reflective response. Reflective defined is characterized by or manifesting careful thought : a thoughtful essay. occupied with or given to thought ; contemplative; meditative; reflective: in a thoughtful mood, careful, heedful, or mindful.

Looking forward to reading each of your posts and comments.

ALSO PLEASE REPLY TO ANOTHER STUDENTS COMMENT BELOW
ALEXANDRIA:

This is a very interesting discussion topic- I believe that overall, the type of error that is of greater concern is dependent upon the area of study. Though, an article by Banerkee et al. (2009) leads me to believe that, because many studies have less willingness to accept a false positive (type I) than a false negative (type II), type I errors would be of greater concern. 

I believe that overall, though, the way each error is handled is more important than the error itself- for instance, if assessments focus more attention on avoiding type I errors, it could lead to a higher prevalence of type II errors, and vice versa. Let's take climate change, for example. Many policy makers and scientists have decided to err on the side of least resistance, avoiding type I errors by not directly associating varying world events with climate change because of unpredictable rates of activities, such as ice sheets melting in Greenland or Antarctica. This avoidance of type I errors could be leading to more type II errors, which could lead to underestimating projections of climate disruptions and lead to the unnecessary loss of lives, livelihoods, or economic damages (Anderegg et al., 2014). 

Reference(s):
Anderegg, W. R. L., Callaway, E. S., Boykoff, M. T., Yohe, G., Root, T. L. (2014). Awarenessof both type 1 and type 2 errors in climate science and assessment. American Meteorological Society, 95(9), 1445-1451.  

Banerjee, A., Chitnis, U. B., Jadhav, S. L., Bhawalkar, J. S. (2009). Hypothesis testing, type I and type II errors. Industrial Psychiatry Journal, 18(2), 127-131. 

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