xx <- rep(1:10,rep(10,10))
yy <- 3 + 2*xx + rnorm(length(xx))
plot(xx,yy)
my.fit <- lm(yy~xx)
abline(my.fit)


system("pwd")
system("ls")
system("ls -l")


system("cd /Users/baileraj/Documents/Bailer")  # note case sensitivity ...
system("pwd")

objects()
save.image("/Users/baileraj/Documents/Bailer/R-class-test.Rdata")


# quit but don’t save image 


# Restart R ...

objects()

load("/Users/baileraj/Documents/Bailer/R-class-test.Rdata")
objects()

# can also save history file and load history file – savehistory/loadhistory

# Packages ...
# to get a new package ...
# .... CRAN website (under “Packages”)
# ...  MENU control Packages > Install packages(s)  [ then you select the package – e.g. Rcmdr ]
# ... ... ... “dependencies=TRUE” often useful since this also installs other packages that are needed
# need to load the package after it is downloaded - “library” function or menu selection Packages > Load packages

# WARNING ... It can take a while to download packages, especially those with lots of dependencies ... 



> names(my.fit)
 [1] "coefficients"  "residuals"     "effects"       "rank"          "fitted.values" "assign"        "qr"           
 [8] "df.residual"   "xlevels"       "call"          "terms"         "model"        
> summary(my.fit)

Call:
lm(formula = yy ~ xx)

Residuals:
     Min       1Q   Median       3Q      Max 
-1.93168 -0.64988  0.00717  0.68510  1.68425 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  3.13884    0.19131   16.41   <2e-16 ***
xx           1.95831    0.03083   63.52   <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 0.8856 on 98 degrees of freedom
Multiple R-squared: 0.9763,    Adjusted R-squared: 0.976 
F-statistic:  4034 on 1 and 98 DF,  p-value: < 2.2e-16 

> anova(my.fit)
Analysis of Variance Table

Response: yy
          Df Sum Sq Mean Sq F value    Pr(>F)    
xx         1 3163.9  3163.9  4034.1 < 2.2e-16 ***
Residuals 98   76.9     0.8                      
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

> summary(yy)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
  3.511   9.414  13.460  13.910  18.530  24.330 
> summary(xx)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
    1.0     3.0     5.5     5.5     8.0    10.0 
> summary(my.fit)

Call:
lm(formula = yy ~ xx)

Residuals:
     Min       1Q   Median       3Q      Max 
-1.93168 -0.64988  0.00717  0.68510  1.68425 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  3.13884    0.19131   16.41   <2e-16 ***
xx           1.95831    0.03083   63.52   <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 0.8856 on 98 degrees of freedom
Multiple R-squared: 0.9763,    Adjusted R-squared: 0.976 
F-statistic:  4034 on 1 and 98 DF,  p-value: < 2.2e-16