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Hi, As I know, regression analysis require normally distributed data. Getis and Ord's Gi* metod interests in only p-values, z score, and gi-index. So you can determine that your values significant or not using p-values, z score, and gi-index. Hi Seda, Thank you so much for your answer! I am still not sure if I can do that just to test whether the data is random or it shows some pattern- I would think so, but I need some proof:). The textbooks I found seem very relaxed in describing these things. I am surprised I was not able to find too much detail... I am still searching for an answer to this... Thanks again!
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02-19-2014
02:19 PM
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Hi everyone, I am not sure if the Moran's I in the ArcGIS package can handle ordinal data, as well. For instance, certain adaptations are necessary to be made for examining spatial autocorrelations in ordinal data using Moran's I. Does the ArcGIS software automatically use the adaptation or it treats ordinal data as if it were continuos data? Thank you very much!
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02-17-2014
09:59 AM
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There is the Joins Count test...but for the life of me I can't find a decent link other that in old text books Hello, For the Moderators: I would like to ask you if you could please verify that I marked the answer by Dan Patterson as helpful. I am not sure why the arrow down seems highlighted - I am not familiar with the forum's system of arrows. I was wondering if you could please make sure the way I marked the answer is consonant with the way I meant it, as I found it very helpful. Thank you so much and I apologize for any inconvenience. Dan, sorry about this and thanks again for your helpful reply!
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02-16-2014
07:38 PM
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Hello, I am so sorry, I meant to click on "this answer was helpful"!!!! please, administrators, could you correct it for me? so sorry about that!!!!
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02-16-2014
07:25 PM
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Hello Dan, Thank you very much for your answer. Yes, that is an option. However, I am mostly interested in looking at high-medium-low type of variables... so I do not know what to do. Thanks!
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02-16-2014
07:23 PM
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Hi everyone, I am wondering if anyone can direct me towards a source where I can find an answer to this question: if the variable I am investigating for spatial autocorrelation is not continuous, is it still appropriate to use Moran's I? I am referring to binary data (e.g. high versus low access to stores) or multinomial data (e.g., high, medium, and low access to stores). The textbooks I consulted indicate that Moran's I can be used for continuous, ordinal, and interval data. However, all examples concern continuous data. I read a paper looking at the spatial autocorrelation in an obesity variable (non-obese versus obese) for individuals living in the same area. I am not sure that is right, based on what I read. Can someone help clarify this issue for me? Thank you very much!
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02-16-2014
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Hello everyone, I have a dataset of respondents (a point dataset) and their responses on a customer satisfaction scale with low, medium, and high categories. I would like to determine hotspots based on their satisfaction. Since Getis and Ord's Gi* test is based on the assumption of normality and my variable is not normally distributed, what test can I use to determine the potential statistically significant hotspots. Thank you very much! Best regards.
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02-16-2014
07:31 AM
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