Statistics/Basic: Difference between revisions

=={{header|R}}==

The challenge of processing a trillion numbers is generating them in the first place. As the errors below show, allocating 7.5 TB for such a vector is simply impractical. The workaround is to generate them, process individual data points and then discard them. The downside in this case is the time.

<lang R>

#Abhishek Ghosh, 10th January 2018

#Generate the sets

a = runif(10,min=0,max=1)

b = runif(100,min=0,max=1)

c = runif(1000,min=0,max=1)

d = runif(10000,min=0,max=1)

#Print out the set of 10 values

cat("a = ",a)

#Print out the Mean and Standard Deviations of each of the sets

cat("Mean of a : ",mean(a))

cat("Standard Deviation of a : ", sd(a))

cat("Mean of b : ",mean(b))

cat("Standard Deviation of b : ", sd(b))

cat("Mean of c : ",mean(c))

cat("Standard Deviation of c : ", sd(c))

cat("Mean of d : ",mean(d))

cat("Standard Deviation of d : ", sd(d))

#Plotting the histogram of d

hist(d)

#Following lines error out due to insufficient memory

cat("Mean of a trillion random values in the range [0,1] : ",mean(runif(10^12,min=0,max=1)))

cat("Standard Deviation of a trillion random values in the range [0,1] : ", sd(runif(10^12,min=0,max=1)))

</lang>

Output

<pre>

a = 0.3884718 0.6324655 0.9288667 0.1948398 0.5636742 0.2746207 0.4712035 0.2624648 0.45492 0.3328236>

Mean of a : 0.4504351

Standard Deviation of a : 0.2171919

Mean of b : 0.5240795

Standard Deviation of b : 0.2654211

Mean of c : 0.5000978

Standard Deviation of c : 0.2882098

Mean of d : 0.4991501

Standard Deviation of d : 0.2911486

Error: cannot allocate vector of size 7450.6 Gb

Error: cannot allocate vector of size 7450.6 Gb

</pre>