Lectures practices

# Create data vector

data=rnorm(50,0,2)
data

##  [1] -3.5047859  0.8075757 -2.4056668  3.5901014 -0.8306277  0.1956667
##  [7]  3.9008111 -1.6585657 -1.9566688 -0.4467344  2.8554834  1.0009904
## [13] -1.5765145 -0.7859562 -2.0202039  2.0961814 -1.6432901  1.8874529
## [19]  2.4373512  0.2882390  0.4774079 -0.1030757 -4.4829954 -0.1726954
## [25] -1.6498459 -1.0352611 -3.6407511 -0.8903669 -0.7724376 -0.7784986
## [31]  0.8981730  2.2394351 -1.0014262 -1.7150598 -0.6690430 -0.2377790
## [37]  0.4220645 -1.2371114  0.6986758 -2.3085811 -0.4959632 -1.1818816
## [43] -0.9210923 -2.7610008 -0.8936850 -1.8346059 -3.2510501  0.8782911
## [49] -0.6428767  1.6205276

boxplot(data)

hist(data)

# Create data vector
# Kolmogorov - Smirnov test
ks.test(data, "pnorm")

## 
##  Exact one-sample Kolmogorov-Smirnov test
## 
## data:  data
## D = 0.30007, p-value = 0.0001727
## alternative hypothesis: two-sided