## [1] 3
R uses vectors.
## [1] 1 4 6
## [1] 1 2 3 4 5 6 7 8 9 10
## [1] 1 5 9 13 17 21 25 29
## [1] 0 0 0 0 0 0 0 0 0 0
When you apply a function to a vector, it usually work on EACH element in the vector.
## [1] 1.4530453 -1.2072829 -0.3514677
## [4] 0.2453460 1.0365689 0.3723902
## [7] 0.5971987 -0.2934279 -0.1469856
## [10] 0.4789901
## [1] 2.11134069 1.45753199 0.12352954
## [4] 0.06019465 1.07447499 0.13867447
## [7] 0.35664627 0.08609995 0.02160475
## [10] 0.22943154
## [1] 2.9060906 -2.4145658 -0.7029354
## [4] 0.4906920 2.0731377 0.7447804
## [7] 1.1943974 -0.5868559 -0.2939711
## [10] 0.9579803
## [1] 4.2761168 0.2990086 0.7036546 1.2780634
## [5] 2.8195262 1.4511992 1.8170216 0.7457030
## [9] 0.8633064 1.6144432
## [1] 0.23517920 0.87486899 1.09611778
## [4] 0.98434840 -0.27236446 0.70784119
## [7] 0.01653147 0.82634676 2.59635950
## [10] 1.61081816
## [1] 10
## [1] 0.8676047
## [1] 0.6731004
## [1] 0.8204269
## Min. 1st Qu. Median Mean 3rd Qu.
## -0.2724 0.3533 0.8506 0.8676 1.0682
## Max.
## 2.5964
### 1. R is case sensitive
X = 3 # This assigns 3 to object X. But you can't see it.
X # now you see what's inside X
x # "x" is not same as "X".
### 2. Vectors
X = c(1, 4, 6) # create vector
X
X = 1:10 # 1 through 10
X
X = seq(1,30, 4) # 1 to 30 in step of 2
X
X = rep(0, 10)
X
# Apply funciton to vector
X = rnorm(10) # draw random sample of size 10 from Standard Normal
X
Y = X ^ 2 # square each number
Y
Y = X * 2 # multiple 2 to each number
Y
Y = exp(X) # take exponential power of each number
Y
### 3. Descriptive statistics
X = rnorm(10) # draw random sample of n=10 from Standard Normal
X
length(X) # get length of X
mean(X) # sample mean
var(X) # variance
sd(X) # Standard Deviation
summary(X) # 5-number summary
# Correlation
X = rnorm(10) # draw random sample of n=10 from Standard Normal
Y = runif(10) # draw random sample of n=10 from Unif(0,1)
cor(X,Y) # correlation between vector X and vector Y