Perform both a Hierarchical and a Non-Hierarchical Cluster analyses, using variables X1–X7 as directed below on the HATCO dataset.Include the following:a)Summarize the results of a Hierarchical...

Objective:
In this assignment, on given data set HATCO a statical analysis will be done by using software SAS. Further data and the result will be interpreted into conclusion. Therefore, this analysis will be involved with both Hierarchical and Non-Hierarchical Cluster analysis using Variable X1 – X7. A MANOVA analyse using Model X9,X10.
Analysis:
a) Hierarchical Model -
b) Non-Hierarchical Model
K = 4
C)
a MANOVA analysis using the following Model: Model X9 X10 = Cluster, to Assess Model Validation by examining how well the4-Cluster category assignments differentiate Purchase Outcomes: X9 (Usagelevel) and X10 (Satisfaction Level)
Cross-Classification Analysis comparing the Cluster group assignments toPurchaser Characteristics variables: X8 (Firm Size), X11 (Specification Buying),X12 (Structure of Procurement), X13 (Type of Industry), and X14 (Type of BuyingSituation); to Profile the Model by examining how well the 4-Cluster category assignments compare and contrast to the associated Purchaser Characteristics.
Interpretation:
1. Hierarchical Model:
Amalgamation Steps
    Step
    Number of
clusters
    Similarity
level
    Distance
level
    Clusters
joined
    New cluster
    Number
of obs.
in new
cluster
    1
    99
    100.000
    0.00000
    15
    20
    15
    2
    2
    98
    98.876
    0.10000
    5
    42
    5
    2
    3
    97
    98.876
    0.10000
    24
    27
    24
    2
    4
    96
    98.410
    0.14142
    47
    61
    47
    2
    5
    95
    97.752
    0.20000
    19
    28
    19
    2
    6
    94
    97.247
    0.24495
    67
    90
    67
    2
    7
    93
    97.026
    0.26458
    36
    41
    36
    2
    8
    92
    97.026
    0.26458
    51
    77
    51
    2
    9
    91
    97.026
    0.26458
    18
    92
    18
    2
    10
    90
    97.026
    0.26458
    33
    62
    33
    2
    11
    89
    96.445
    0.31623
    25
    44
    25
    2
    12
    88
    96.445
    0.31623
    85
    87
    85
    2
    13
    87
    96.445
    0.31623
    43
    46
    43
    2
    14
    86
    96.445
    0.31623
    65
    79
    65
    2
    15
    85
    95.947
    0.36056
    38
    63
    38
    2
    16
    84
    95.504
    0.40000
    69
    81
    69
    2
    17
    83
    95.100
    0.43589
    50
    72
    50
    2
    18
    82
    95.100
    0.43589
    56
    91
    56
    2
    19
    81
    95.100
    0.43589
    94
    98
    94
    2
    20
    80
    94.728
    0.46904
    1
    95
    1
    2
    21
    79
    94.728
    0.46904
    16
    73
    16
    2
    22
    78
    94.728
    0.46904
    75
    99
    75
    2
    23
    77
    94.728
    0.46904
    37
    48
    37
    2
    24
    76
    94.380
    0.50000
    11
    100
    11
    2
    25
    75
    94.052
    0.52915
    4
    89
    4
    2
    26
    74
    94.052
    0.52915
    84
    88
    84
    2
    27
    73
    94.052
    0.52915
    23
    32
    23
    2
    28
    72
    94.052
    0.52915
    2
    83
    2
    2
    29
    71
    94.052
    0.52915
    29
    78
    29
    2
    30
    70
    94.052
    0.52915
    3
    71
    3
    2
    31
    69
    93.071
    0.61644
    17
    64
    17
    2
    32
    68
    92.629
    0.65574
    8
    68
    8
    2
    33
    67
    92.629
    0.65574
    12
    76
    12
    2
    34
    66
    91.816
    0.72801
    9
    74
    9
    2
    35
    65
    91.439
    0.76158
    52
    60
    52
    2
    36
    64
    90.799
    0.81854
    10
    34
    10
    2
    37
    63
    90.595
    0.83666
    26
    59
    26
    2
    38
    62
    89.698
    0.91652
    49
    97
    49
    2
    39
    61
    89.277
    0.95394
    7
    67
    7
    3
    40
    60
    88.929
    0.98489
    36
    84
    36
    4
    41
    59
    88.536
    1.01980
    13
    21
    13
    2
    42
    58
    88.481
    1.02470
    40
    54
    40
    2
    43
    57
    88.481
    1.02470
    82
    93
    82
    2
    44
    56
    88.372
    1.03441
    66
    80
    66
    2
    45
    55
    88.210
    1.04881
    10
    30
    10
    3
    46
    54
    88.104
    1.05830
    22
    55
    22
    2
    47
    53
    87.085
    1.14891
    6
    70
    6
    2
    48
    52
    85.517
    1.28841
    45
    86
    45
    2
    49
    51
    85.430
    1.29615
    39
    96
    39
    2
    50
    50
    84.711
    1.36015
    50
    69
    50
    4
    51
    49
    83.251
    1.48997
    10
    53
    10
    4
    52
    48
    82.405
    1.56525
    14
    38
    14
    3
    53
    47
    82.050
    1.59687
    15
    19
    15
    4
    54
    46
    81.701
    1.62788
    13
    35
    13
    3
    55
    45
    81.224
    1.67033
    16
    29
    16
    4
    56
    44
    79.986
    1.78045
    4
    24
    4
    4
    57
    43
    79.704
    1.80555
    18
    50
    18
    6
    58
    42
    79.060
    1.86279
    40
    45
    40
    4
    59
    41
    79.060
    1.86279
    9
    58
    9
    3
    60
    40
    78.701
    1.89473
    31
    37
    31
    3
    61
    39
    78.554
    1.90788
    25
    33
    25
    4
    62
    38
    77.574
    1.99499
    8
    36
    8
    6
    63
    37
    77.546
    1.99750
    56
    75
    56
    4
    64
    36
    76.421
    2.09762
    25
    26
    25
    6
    65
    35
    75.891
    2.14476
    14
    66
    14
    5
    66
    34
    75.578
    2.17256
    6
    52
    6
    4
    67
    33
    74.890
    2.23383
    3
    10
    3
    6
    68
    32
    74.839
    2.23830
    9
    12
    9
    5
    69
    31
    74.441
    2.27376
    11
    85
    11
    4
    70
    30
    73.423
    2.36432
    1
    51
    1
    4
    71
    29
    73.116
    2.39165
    39
    65
    39
    4
    72
    28
    72.719
    2.42693
    7
    15
    7
    7
    73
    27
    72.650
    2.43311
    2
    56
    2
    6
    74
    26
    72.580
    2.43926
    13
    22
    13
    5
    75
    25
    72.328
    2.46171
    18
    43
    18
    8
    76
    24
    72.237
    2.46982
    40
    94
    40
    6
    77
    23
    70.174
    2.65330
    16
    47
    16
    6
    78
    22
    67.909
    2.85482
    3
    31
    3
    9
    79
    21
    67.401
    2.90000
    11
    14
    11
    9
    80
    20
    65.135
    3.10161
    8
    17
    8
    8
    81
    19
    65.045
    3.10966
    7
    9
    7
    12
    82
    18
    64.064
    3.19687
    4
    40
    4
    10
    83
    17
    62.196
    3.36303
    23
    57
    23
    3
    84
    16
    61.847
    3.39411
    18
    25
    18
    14
    85
    15
    61.452
    3.42929
    4
    39
    4
    14
    86
    14
    56.319
    3.88587
    1
    13
    1
    9
    87
    13
    56.074
    3.90768
    18
    49
    18
    16
    88
    12
    55.902
    3.92301
    2
    6
    2
    10
    89
    11
    54.547
    4.04351
    11
    16
    11
    15
    90
    10
    54.505
    4.04722
    3
    23
    3
    12
    91
    9
    47.216
    4.69574
    2
    8
    2
    18
    92
    8
    45.542
    4.84458
    11
    18
    11
    31
    93
    7
    44.851
    4.90612
    3
    82
    3
    14
    94
    6
    42.660
    5.10098
    1
    11
    1
    40
    95
    5
    38.287
    5.48999
    2
    4
    2
    32
    96
    4
    32.930
    5.96657
    5
    7
    5
    14
    97
    3
    19.567
    7.15542
    2
    3
    2
    46
    98
    2
    17.419
    7.34643
    1
    5
    1
    54
    99
    1
    0.000
    8.89607
    1
    2
    1
    100
2. Non-Hierarchical Model
K = 4
Cluster Centroids
    Variable
    Cluster1
    Cluster2
    Cluster3
    Cluster4
    Grand
centroid
     
     
     
     
     
     
    Delivery speed
    4.1441
    2.0241
    3.6143
    4.4043
    3.5150
    Price Level
    1.5794
    2.7655
    4.1286
    1.9435
    2.3640
    Price flexibility
    8.6353
    6.9414
    5.9500
    9.1826
    7.8940
    Manufacture_s image
    4.4176
    5.1621
    6.0643
    6.0870
    5.2480
    Service
    2.8353
    2.3655
    3.8429
    3.1652
    2.9160
    Salesforce_s image
    2.0882
    2.5552
    3.1643
    3.3522
    2.6650
    Product Quality
    5.3147
    8.2690
    7.9500
    7.1870
    6.9710
    
    
    
    
    
    
3. MANOVA
    Null hypothesis
    All means are equal
    Alternative hypothesis
    Not all means are equal
    Significance level
    α = 0.05
Equal variances were assumed for the analysis.
Factor Information
    Factor
    Levels
    Values
    Factor
    2
    Size of firm, Usage Level
Analysis of Variance
    Source
    DF
    Adj SS
    Adj MS
    F-Value
    P-Value
    Factor
    1
    104425
    104425
    2577.10
    0.000
    Error
    198
    8023
    41
     
     
    Total
    199
    112448
     
     
     
    
    
    
    
    
    
Model Summary
    S
    R-sq
    R-sq(adj)
    R-sq(pred)
    6.36555
    92.87%
    92.83%
    92.72%
Means
    Factor
    N
    Mean
    StDev
    95% CI
    Size of firm
    100
    0.4000
    0.4924
    (-0.8553, 1.6553)
    Usage Level
    100
    46.100
    8.989
    (44.845, 47.355)
Pooled StDev = 6.36555
Results:
1. Hierarchical:
Final Partition
    
    Number of
observations
    Within
cluster sum
of squares
    Average
distance
from
centroid
    Maximum
distance
from
centroid
    Cluster1
    100
    994.752
    3.04964
    5.27503
2. Non-Hierarchical:
Final Partition
    
    Number of
observations
    Within
cluster sum
of squares
    Average
distance
from
centroid
    Maximum
distance
from
centroid
     
     
     
     
     
    Cluster1
    34
    151.502
    2.079
    2.928
    Cluster2
    29
    119.197
    1.984
    2.854
    Cluster3
    14
    54.234
    1.833
    3.051
    Cluster4
    23
    109.941
    2.031
    3.947
Distances Between Cluster Centroids
    
    Cluster1
    Cluster2
    Cluster3
    Cluster4
     
     
     
     
     
    Cluster1
    0.0000
    4.3001
    5.0812
    2.9152
    Cluster2
    4.3001
    0.0000
    2.9730
    3.8295
    Cluster3
    5.0812
    2.9730
    0.0000
    4.1141
    Cluster4
    2.9152
    3.8295
    4.1141
    0.0000
3. MANOVA
Tukey Pairwise Comparisons
Grouping Information Using the Tukey Method and 95% Confidence
    Factor
    N
    Mean
    Grouping
    Usage Level
    100
    46.100
    A
     
    Size of firm
    100
    0.4000
     
    B
Means that do not share a letter are significantly different.
Hsu Multiple Comparisons with the Best (MCB)
Conclusion:
Parameters
    Response
    Goal
    Lower
    Target
    Upper
    Weight
    Importance
    Size of firm
    Maximum
    0
    1
     
    1
    1
    Solution
    Solution
    Specification
buying
    Structure of
procurement
    Type of
industry
    Type of
buying
situation
    Size of firm
Fit
    Composite
Desirability
    1
    0
    1
    1
    3
    1
    1
Multiple Response Prediction
    Variable
    Setting
    Specification buying
    0
    Structure of procurement
    1
    Type of industry
    1
    Type of buying situation
    3
    
    
    Response
    Fit
    SE Fit
    95% CI
    95% PI
    Size of firm
    1.000
    0.000
    (1.000, 1.000)
    (1.000, 1.000)
Appendix:
Code Snippet 1 - MANOVA
/*---------------------------------------------------------
The options statement below should be placed
before the data step when submitting this code.
---------------------------------------------------------*/
options VALIDMEMNAME=EXTEND VALIDVARNAME=ANY;
/*------------------------------------------
Generated SAS Scoring Code
Date : 18Dec2022:05:15:22
Locale : en_US
Model Type : Linear Regression
Interval variable: Size of firm
Interval variable: Specification buying
Interval variable: Structure of procurement
Interval variable: Type of industry
Interval variable: Type of buying situation
Response variable: Size of firm
------------------------------------------*/
/*---------------------------------------------------------
Generated SAS Scoring Code
Date: 18Dec2022:05:15:22
...