# [R] Exercise in R

Bert Gunter bgunter.4567 at gmail.com
Sat Jun 10 05:44:49 CEST 2017

```We don't do homework here. Ask your professor for help.

Cheers,
Bert

Bert Gunter

"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )

On Fri, Jun 9, 2017 at 9:10 AM, Alex Ferrara <Rikushadow at hotmail.it> wrote:
> Hi i need some help with this exercise:
>
> FIles: https://mega.nz/#!JxMFGIwC!qA85SBIBRVagCzYfmLwSvGuNK_qXqCXrakPxXryCpGg
>
> #PARZIAL 3: GEO
>
> #Data:
> # Shapefile "INCOME" contains dummy information about revenue
> # Common Abbreviations in the "INCOME" variable and the centroid altitude
> #dell common in the variable "ALT"
>
> #Richieste
>
> # 1
> #map of the variable "INCOME", choosing an appropriate color scale (save the map in pdf)
>
> #2
> #map of the variable "ALT", choosing a color palette from green to white, passing for brown (save the map in pdf)
>
> # 3
> #calculate the confidence interval of the pearson correlation coefficient between the variables considered
>
> # 4
> # Graph (and save in pdf) the relationship between variables via scatterplot,
> #Set the graphic parameters appropriately and enter the correlation value in the title
> #del previous point
>
> # 5
> #Comment what appears from the analysis performed
>
> # 6
> # Find a way to map variables on the same scale so that it is obvious
> #the correlation found. (Suggestion: to use transformation, and possibly reversal of signs)
>
> # 7
> #fit a linear model that explains the income in function of altitude (original scales)
>
> # 8
> #load the metered values and those observed on the same scale
>
> # 9
> #wrap the gap between residual and observed and write the instructions that they print
> # Consoles municipalities with the worst estimate (below and above estimated)
>
> How should i do? Thanks for reply
>
>
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>
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