From the theory of SVD’s we know G can be decomposed as a sum of rank-many rankone matrices. Suppose that G is approximated by a rank-one matrix sqT with s ∈ Rn and q ∈ Rm with non-negative components. Can you use this fact to give a difficulty score or rating? What is the possible meaning of the vector s? Note one can use the top singular value decomposition to get this score vector!

30 people weigh 160 pounds or more

whew you’re speaking a different language

school a:

minimum value is 2

maximum value is 22

the lower quartile is 2.5

the median is 10

the upper quartile is 15.5

school b:

minimum value is 9

maximum value is 20

the lower quartile is 12

the median is 16

the upper quartile is 18

box plot for school a isn't symmetrical. the data tails on the right

box plot for school b isn't symmetrical. the data tails on the left

hope i

-lavira: )