### General Code for running a regression in R


### import the data


datum=read.csv(file.choose()) #imports data
# Note that the data file must be saved as a csv file
# The imported data object will be called 'datum'


### Make sure the data imported correctly


head(datum) #displays the column headings of data plus first 6 rows


### Plot Data


plot(Y~X,data=datum) #plots the data. Be sure to replace 'Y' with the response variable
### and 'X' with the x-variable from your excel file. 


### Run regression analysis


results=lm(Y~X,data=datum) #runs a regression
# Note that R won't seem to do anything, instead it is creating a new
# object called 'results' that contains the important information
# 'Y' is the response in your excel file. BE SURE TO CHANGE THE NAME
# 'X' is the x-variable in your excel file. BE SURE TO CHANGE THE NAME


### Get the information from the 'results' object


summary(results) # gives output.


###Example output

#Call:
#lm(formula = Understory ~ Canopy, data = datum)
#
#Residuals:
#    Min      1Q  Median      3Q     Max 
#-18.203  -3.203   1.087   3.419  13.189 
#
#Coefficients:
#            Estimate Std. Error t value Pr(>|t|)    
#(Intercept)  51.5253     2.5345  20.329  < 2e-16 ***   ###Estimate is Beta0
#Canopy       -1.1576     0.1518  -7.626 9.27e-10 ***   ### Estmate is Beta1 and p-value for test of H0: slope=0
#---
#Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 
#
#Residual standard error: 6.676 on 47 degrees of freedom   #This is the estimate of sigma
#Multiple R-squared: 0.553,      Adjusted R-squared: 0.5435 
#F-statistic: 58.15 on 1 and 47 DF,  p-value: 9.271e-10   


###Plot line on plot
abline(results) #where 'results' is an lm object




### Get information from ANOVA table


anova(results) # gives similar results in ANOVA table format