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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