Message-ID: <HE1PR08MB108285690576B22E8AA2B4F7B0CE0@HE1PR08MB1082.eurprd08.prod.outlook.com>
Date: 2017-06-09T16:10:54Z
From: Alex Ferrara
Subject: Exercise in R
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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