The deviation tells us how far a given point is from the mean value. Why doesn't the sum of deviations tell us anything useful about the overall dispersion of the data. Because the sum of deviations from the mean is by definition zero in all cases. Because calculation of the mean is arithmetic but the corresponding deviations are geometric, so a simple linear sum would tell us nothing. Because there is no apriori expectation of any particular distribution of deviations that can be anticipated from the raw data.
The deviation tells us how far a given point is from the mean value. Why doesn't the sum of deviations tell us anything useful about the overall dispersion of the data. Because the sum of deviations from the mean is by definition zero in all cases. Because calculation of the mean is arithmetic but the corresponding deviations are geometric, so a simple linear sum would tell us nothing. Because there is no apriori expectation of any particular distribution of deviations that can be anticipated from the raw data.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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![The deviation tells us how far a given point is from the mean value. Why doesn't the
sum of deviations tell us anything useful about the overall dispersion of the data.
Because the sum of deviations from the mean is by definition zero in all cases.
Because calculation of the mean is arithmetic but the corresponding deviations
are geometric, so a simple linear sum would tell us nothing.
Because there is no apriori expectation of any particular distribution of
deviations that can be anticipated from the raw data.
Because not everything that seems like it should be useful is actually useful.
Look at our instructor for example.
All of the above.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F81d29c03-5161-4e8e-805d-f0c3f57e18ca%2Fe18bfcdb-12a1-42e2-b401-dff393c3dfcb%2Fidr6d3b_processed.png&w=3840&q=75)
Transcribed Image Text:The deviation tells us how far a given point is from the mean value. Why doesn't the
sum of deviations tell us anything useful about the overall dispersion of the data.
Because the sum of deviations from the mean is by definition zero in all cases.
Because calculation of the mean is arithmetic but the corresponding deviations
are geometric, so a simple linear sum would tell us nothing.
Because there is no apriori expectation of any particular distribution of
deviations that can be anticipated from the raw data.
Because not everything that seems like it should be useful is actually useful.
Look at our instructor for example.
All of the above.
![Nearest Neighbour Analysis can produce errors if a point near the boundary has a
nearest neighbour that is outside of the boundaries of the study area. This problem
can be addressed by:
1) Create a buffer around your study region.
2) Include points in the buffer zone as nearest neighbours to points inside the study.
3) Check to make sure none of the new points have a nearest neighbor that is
outside the buffer zone.
True
False](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F81d29c03-5161-4e8e-805d-f0c3f57e18ca%2Fe18bfcdb-12a1-42e2-b401-dff393c3dfcb%2Fqm4124c_processed.png&w=3840&q=75)
Transcribed Image Text:Nearest Neighbour Analysis can produce errors if a point near the boundary has a
nearest neighbour that is outside of the boundaries of the study area. This problem
can be addressed by:
1) Create a buffer around your study region.
2) Include points in the buffer zone as nearest neighbours to points inside the study.
3) Check to make sure none of the new points have a nearest neighbor that is
outside the buffer zone.
True
False
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