The information is already organized in a tabular form, so we can copy the entries from the table to form a matrix.
3& 2& 2& 1
4& 3& 2& 3
5& 5& 4& 4
1& 5& 5& 2
b
Let's highlight the highest score in each column of the table.
Brand
Cost
Comfort
Look
Longevity
A
3
2
2
1
B
4
3
2
3
C
5
5
4
4
D
1
5
5
2
We can see that in two categories brand C was rated highest, in one category it is tied at first place for the top score, and in the fourth category it is at second place.
Based on this information, brand C can be considered the best buy.
c
Let's look at the row and column sums separately.
Row Sum
If we divide the sum of the elements in the rows by 4, this average score can be considered the overall score of that particular brand.
Brand
Cost
Comfort
Look
Longevity
Average
A
3
2
2
1
2
B
4
3
2
3
3
C
5
5
4
4
4.5
D
1
5
5
2
3.25
This can be a useful information for consumers.
Note, that this average score also indicates that brand C is a good buy, which is what we found in Part B.
Column Sum
Comparing the average based on the column sums with the individual scores may give some indication to manufacturers how their product compares to the competitor's.
Brand
Cost
Comfort
Look
Longevity
A
3
2
2
1
B
4
3
2
3
C
5
5
4
4
D
1
5
5
2
Average
3.25
3.75
3.25
2.5
If the full table is not shown to the companies and instead just the column averages and the row relevant to their product are shown, this can be useful information.
