A B D E F G H K 1 MEDV 10 14 15 16 12345678901234557 ZN INDUS CHAS NOX RM AGE DIS RAD PTRATIO CRIM TAX 22.9 40 1.25 No 0.42 6.49 44.4 8.79 1.2 19.7 0.06 335 24.1 60 1.69 No 0.41 6.57 35.9 10.7 4.3 18.6 60 1.69 No 0.41 5.88 18.5 10.7 4.5 35 18.3 0.07 411 18.3 0.07 411 30.1 90 2.02 No 0.41 6.72 12.1 5.5 17 0.01 187 18.2 80 1.91 No 0.41 5.66 21.9 10.5 4.2 22 0.04 334 20.6 80 1.91 No 0.41 19.5 10.5 4.3 22 0.1 334 17.8 0 18.1 Yes 0.77 6.21 97.4 2.12 24.5 20.2 8.98 666 21.7 0 18.1 Yes 0.77 6.39 91 2.5 24.6 20.2 3.84 666 22.7 0 ? Yes 0.77 6.12 83.4 2.72 24.7 20.2 5.2 666 11 22.6 0 18.1 No 0.77 0 81.3 2.5 24.4 20.2 4.26 666 12 19.9 0 18.1 No 0.77 6.25 91.1 2.29 24.3 3.83 666 13 20.8 0 18.1 No 0.77 5.36 96.2 2.1 24.1 20.2 3.67 666 16.8 Yes 7.12 1.8 21.9 17 21.9 ooo 0 18.1 Yes 0.71 8.78 82.9 1.9 24.3 20.2 3.47 666 0 18.1 No 0.71 3.56 87.9 1.61 24.4 20.2 4.55 666 0 18.1 No 0.71 4.96 91.4 1.75 24.1 20.2 3.69 666
A B D E F G H K 1 MEDV 10 14 15 16 12345678901234557 ZN INDUS CHAS NOX RM AGE DIS RAD PTRATIO CRIM TAX 22.9 40 1.25 No 0.42 6.49 44.4 8.79 1.2 19.7 0.06 335 24.1 60 1.69 No 0.41 6.57 35.9 10.7 4.3 18.6 60 1.69 No 0.41 5.88 18.5 10.7 4.5 35 18.3 0.07 411 18.3 0.07 411 30.1 90 2.02 No 0.41 6.72 12.1 5.5 17 0.01 187 18.2 80 1.91 No 0.41 5.66 21.9 10.5 4.2 22 0.04 334 20.6 80 1.91 No 0.41 19.5 10.5 4.3 22 0.1 334 17.8 0 18.1 Yes 0.77 6.21 97.4 2.12 24.5 20.2 8.98 666 21.7 0 18.1 Yes 0.77 6.39 91 2.5 24.6 20.2 3.84 666 22.7 0 ? Yes 0.77 6.12 83.4 2.72 24.7 20.2 5.2 666 11 22.6 0 18.1 No 0.77 0 81.3 2.5 24.4 20.2 4.26 666 12 19.9 0 18.1 No 0.77 6.25 91.1 2.29 24.3 3.83 666 13 20.8 0 18.1 No 0.77 5.36 96.2 2.1 24.1 20.2 3.67 666 16.8 Yes 7.12 1.8 21.9 17 21.9 ooo 0 18.1 Yes 0.71 8.78 82.9 1.9 24.3 20.2 3.47 666 0 18.1 No 0.71 3.56 87.9 1.61 24.4 20.2 4.55 666 0 18.1 No 0.71 4.96 91.4 1.75 24.1 20.2 3.69 666
Chapter6: System Integration And Performance
Section: Chapter Questions
Problem 2PE
Related questions
Question
(Short-answer) b. Continue from the previous question. Suppose part of the data you extracted from the data warehouse is the following. Identify the missing values you think exist in the dataset. Use Column letter and Row number to refer to each missing value in the dataset. Please write down how you want to address each particular missing value (you can group them if they receive same treatment). For imputation, you do not need to calculate the exact imputed values but just describe what kind of value you want to use to impute.
Transcribed Image Text:A
B
D
E
F
G
H
K
1 MEDV
10
14
15
16
12345678901234557
ZN
INDUS
CHAS
NOX
RM
AGE
DIS
RAD
PTRATIO
CRIM
TAX
22.9
40
1.25
No
0.42
6.49
44.4
8.79
1.2
19.7
0.06
335
24.1
60
1.69
No
0.41
6.57
35.9
10.7
4.3
18.6
60
1.69
No
0.41
5.88
18.5
10.7
4.5
35
18.3
0.07
411
18.3
0.07
411
30.1
90
2.02
No
0.41
6.72
12.1
5.5
17
0.01
187
18.2
80
1.91
No
0.41
5.66
21.9
10.5
4.2
22
0.04
334
20.6
80
1.91
No
0.41
19.5
10.5
4.3
22
0.1
334
17.8
0
18.1
Yes
0.77
6.21
97.4
2.12
24.5
20.2
8.98
666
21.7
0
18.1
Yes
0.77
6.39
91
2.5
24.6
20.2
3.84
666
22.7
0
?
Yes
0.77
6.12
83.4
2.72
24.7
20.2
5.2
666
11 22.6
0
18.1
No
0.77
0
81.3
2.5
24.4
20.2
4.26
666
12 19.9
0
18.1
No
0.77
6.25
91.1
2.29
24.3
3.83
666
13 20.8
0
18.1
No
0.77
5.36
96.2
2.1
24.1
20.2
3.67
666
16.8
Yes
7.12
1.8
21.9
17 21.9
ooo
0
18.1
Yes
0.71
8.78
82.9
1.9
24.3
20.2
3.47
666
0
18.1
No
0.71
3.56
87.9
1.61
24.4
20.2
4.55
666
0
18.1
No
0.71
4.96
91.4
1.75
24.1
20.2
3.69
666
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