DESCRIPTION

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QUESTION

(25 pts) Fill in the blank: Reducing the number of variables in a
quantitative analysis is called ________________ reduction.

QUESTION -ext .R -run 'Rscript omsi_answer2.R'

(25 pts) In the Turkish Evaluations data, consider the weights in PC3.
Which survey question has the largest weight (in absolute value)?  Your
answer will be a number in 1,2,...,28.  Fill in the blanks.

maxQ <- function() 
{
   turk <- read.csv('turkiye-student-evaluation_R_Specific.csv')

}

print(maxQ())

QUESTION -ext .R -run 'Rscript omsi_answer3.R'

(25 pts) Find the weight that PC3 places on the eighth evaluation in the
original data in the Turkish Evaluations dataset.  Fill in the blanks.

wt38 <- function() 
{
   turk <- read.csv('turkiye-student-evaluation_R_Specific.csv')

}

print(wt38())

QUESTION -ext .R -run 'Rscript omsi_answer4.R'

(25 pts) Write a function that calculates row i of the matrix product
WH.  (Motivation:  In the matrix factorization method for recommender
systems with A approx= WH, row i would be the entire set of predicted
movie ratings for user i.) For full credit, you must avoid using loops.
Fill in the blanks.
oneRow <- function(w,h,i) 
{

}

a <- rbind(1:3,c(5,1,8))
b <- rbind(c(1,2,10),c(4,12,0),c(0,0,1)) 
print(oneRow(a,b,2)) # prints (9,22,58)