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Output2

• Log

o Log • Discriminant

o Active Dataset

o Analysis Case Processing Summary

o Group Statistics

o Tests of Equality of Group Means o Analysis 1 ▪ Box's Test of Equality of Covariance Matrices

▪ Log Determinants

▪ Test Results ▪ Stepwise Statistics

▪ Variables Entered/Removed

▪ Variables in the Analysis

▪ Variables Not in the Analysis

▪ Wilks' Lambda ▪ Summary of Canonical Discriminant Functions

▪ Eigenvalues

▪ Wilks' Lambda

▪ Standardized Canonical Discriminant Function Coeff...

▪ Structure Matrix

▪ Canonical Discriminant Function Coefficients ▪ Functions at Group Centroids ▪ Classification Statistics

▪ Classification Processing Summary

▪ Prior Probabilities for Groups

▪ Classification Function Coefficients

▪ Territorial Map

▪ Casewise Statistics

▪ Classification Results

Log Log - Log - November 6, 2018

DISCRIMINANT /GROUPS=X1(1 3) /VARIABLES=X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17 X18 /ANALYSIS ALL /SAVE=CLASS SCORES PROBS /METHOD=MAHAL /FIN=3.84 /FOUT=2.71 /PRIORS EQUAL /HISTORY /STATISTICS=MEAN STDDEV UNIVF BOXM COEFF RAW CROSSV ALID /PLOT=MAP /PLOT=CASES /CLASSIFY=NONMISSING POOLED.

Discriminant Discriminant - Active Dataset - November 6, 2018

[DataSet1] /Desktop/Education/MSCM Program/Fall Semester/SCM Research Method/Lecture Notes/Mult ivariate Lectures /Data Analysis SPSS/Discriminant Analysis/HBAT.sav

Discriminant Discriminant - Analysis Case Processing Summary - November 6, 2018

Analysis Case Processing SummaryAnalysis Case Processing Summary, table, 1 levels of column headers and 2 levels of row headers, table with 4 columns and 8 rows Unweighted Cases N Percent Valid 100 100.0 Missing or out-of- 0 .0 range group codes At least one missing 0 .0 discriminating variable Excluded Both missing or out- of-range group codes and at least one 0 .0 missing discriminating variable Total 0 .0 Total 100 100.0

Discriminant Discriminant - Group Statistics - November 6, 2018

Group StatisticsGroup Statistics, table, 2 levels of column headers and 2 levels of row headers, table with 6 columns and 55 rows

Std. Valid N (listwise) X1 Mean Deviation Unweighted Weighted X6 7.097 1.0219 32 32.000 X7 3.675 .6998 32 32.000 X8 5.091 1.6747 32 32.000 1 X9 4.350 .9333 32 32.000 X10 3.725 1.0122 32 32.000 X11 4.831 1.0532 32 32.000 X12 4.863 .9517 32 32.000 X13 7.491 1.2830 32 32.000 X14 5.894 .9442 32 32.000 X15 5.144 1.6582 32 32.000 X16 3.559 .8728 32 32.000 X17 4.234 1.0012 32 32.000 X18 3.172 .6150 32 32.000 X6 7.240 1.3720 35 35.000 X7 3.780 .6521 35 35.000 X8 5.391 1.5056 35 35.000 X9 5.943 .8876 35 35.000 X10 4.277 1.1083 35 35.000 X11 5.603 .9922 35 35.000 2 X12 5.431 .9539 35 35.000 X13 7.557 1.3834 35 35.000 X14 5.977 .8178 35 35.000 X15 4.940 1.3574 35 35.000 X16 4.649 .7493 35 35.000 X17 5.523 1.1840 35 35.000 X18 4.243 .5731 35 35.000 X6 9.106 .6509 33 33.000 X7 3.555 .7517 33 33.000 X8 5.603 1.4095 33 33.000 X9 5.970 1.0406 33 33.000 X10 4.003 1.2133 33 33.000 X11 6.964 .9243 33 33.000 3 X12 5.048 1.2392 33 33.000 X13 5.855 1.3514 33 33.000 X14 6.258 .6558 33 33.000 X15 5.379 1.4741 33 33.000 X16 4.582 .7568 33 33.000 X17 4.006 .7814 33 33.000 X18 4.200 .4500 33 33.000 X6 7.810 1.3963 100 100.000 X7 3.672 .7005 100 100.000 X8 5.365 1.5305 100 100.000 X9 5.442 1.2084 100 100.000 Total X10 4.010 1.1269 100 100.000 X11 5.805 1.3153 100 100.000 X12 5.123 1.0723 100 100.000 X13 6.974 1.5451 100 100.000 X14 6.043 .8197 100 100.000 X15 5.150 1.4930 100 100.000 X16 4.278 .9288 100 100.000 X17 4.610 1.2060 100 100.000 X18 3.886 .7344 100 100.000

Discriminant Discriminant - Tests of Equality of Group Means - November 6, 2018

Tests of Equality of Group MeansTests of Equality of Group Means, table, 1 levels of column headers and 1 levels of row headers, table with 6 columns and 15 rows Wilks' F df1 df2 Sig. Lambda X6 .570 36.652 2 97 .000 X7 .982 .878 2 97 .419 X8 .981 .917 2 97 .403 X9 .612 30.782 2 97 .000 X10 .959 2.050 2 97 .134 X11 .556 38.758 2 97 .000 X12 .950 2.549 2 97 .083 X13 .739 17.172 2 97 .000 X14 .964 1.803 2 97 .170 X15 .985 .730 2 97 .485 X16 .715 19.372 2 97 .000 X17 .682 22.563 2 97 .000 X18 .550 39.681 2 97 .000

Box's Test of Equality of Covariance Matrices Box's Test of Equality of Covariance Matrices - Log Determinants - November 6, 2018

Log DeterminantsLog Determinants, table, 1 levels of column headers and 1 levels of row headers, table with 3 columns and 7 rows X1 Rank Log Determinant 1 3 -.218 2 3 .027 3 3 -2.011 Pooled within- 3 -.321 groups The ranks and natural logarithms of determinants printed are those of the group covariance matrices.

Box's Test of Equality of Covariance Matrices Box's Test of Equality of Covariance Matrices - Test Results - November 6, 2018

Test ResultsTest Results, table, 0 levels of column headers and 2 levels of row headers, table with 3 columns and 7 rows Box's M 38.988 Approx. 3.103 df1 12 F df2 45025.475 Sig. .000 Tests null hypothesis of equal population covariance matrices.

Stepwise Statistics Stepwise Statistics - Variables Entered/Removed - November 6, 2018

a,b,c,d Variables Entered/Removed Variables Entered/Removed, table, 3 levels of column headers and 1 levels of row headers, table with 8 columns and 12 rows

Min. D Squared Step Entered Between Exact F Statistic Groups Statistic df1 df2 Sig. 1 X11 .607 1 and 2 10.141 1 97.000 .002 2 X17 2.919 2 and 3 24.531 2 96.000 2.481E-9 3 X6 4.599 2 and 3 25.501 3 95.000 3.455E-12 At each step, the variable that maximizes the Mahalanobis distance between the two closest groups is entered. a. Maximum number of steps is 26. b. Minimum partial F to enter is 3.84. c. Maximum partial F to remove is 2.71. d. F level, tolerance, or VIN insufficient for further computation.

Stepwise Statistics Stepwise Statistics - Variables in the Analysis - November 6, 2018

Variables in the AnalysisVariables in the Analysis, table, 1 levels of column headers and 2 levels of row headers, table with 6 columns and 8 rows Min. D Between Step Tolerance F to Remove Squared Groups 1 X11 1.000 38.758 X11 .816 42.732 .051 1 and 3 2 X17 .816 25.892 .607 1 and 2 X11 .807 31.443 2.271 1 and 2 3 X17 .651 30.587 .609 1 and 2 X6 .789 22.058 2.919 2 and 3

Stepwise Statistics Stepwise Statistics - Variables Not in the Analysis - November 6, 2018

Variables Not in the AnalysisVariables Not in the Analysis, table, 1 levels of column headers and 2 levels of row headers, table with 7 columns and 48 rows Min. Min. D Between Step Tolerance F to Enter Tolerance Squared Groups X6 1.000 1.000 36.652 .018 1 and 2 X7 1.000 1.000 .878 .022 1 and 2 X8 1.000 1.000 .917 .019 2 and 3 X9 1.000 1.000 30.782 .001 2 and 3 X10 1.000 1.000 2.050 .060 2 and 3 X11 1.000 1.000 38.758 .607 1 and 2 0 X12 1.000 1.000 2.549 .031 1 and 3 X13 1.000 1.000 17.172 .002 1 and 2 X14 1.000 1.000 1.803 .011 1 and 2 X15 1.000 1.000 .730 .019 1 and 2 X16 1.000 1.000 19.372 .007 2 and 3 X17 1.000 1.000 22.563 .051 1 and 3 X18 1.000 1.000 39.681 .006 2 and 3 X6 .988 .988 17.822 .609 1 and 2 X7 1.000 1.000 .736 .627 1 and 2 X8 .980 .980 .064 .614 1 and 2 X9 .831 .831 16.633 2.232 2 and 3 X10 .994 .994 2.333 .918 1 and 2 X12 .987 .987 3.005 1.007 1 and 2 1 X13 .920 .920 5.364 .686 1 and 2 X14 .959 .959 .043 .610 1 and 2 X15 1.000 1.000 .624 .623 1 and 2 X16 .932 .932 11.120 2.074 1 and 2 X17 .816 .816 25.892 2.919 2 and 3 X18 .761 .761 25.094 2.623 2 and 3 X6 .789 .651 22.058 4.599 2 and 3 X7 .923 .753 .888 2.921 2 and 3 X8 .947 .789 .921 2.979 2 and 3 X9 .409 .401 1.008 2.956 2 and 3 X10 .906 .744 .217 2.948 2 and 3 2 X12 .912 .754 .213 2.924 2 and 3 X13 .826 .733 3.978 3.310 2 and 3 X14 .954 .797 .031 2.919 2 and 3 X15 .957 .781 2.041 3.198 2 and 3 X16 .614 .538 .585 2.945 2 and 3 X18 .045 .045 2.781 3.197 2 and 3 X7 .921 .604 .948 4.612 2 and 3 X8 .942 .626 1.102 4.620 2 and 3 X9 .406 .343 .294 4.607 2 and 3 X10 .902 .594 .030 4.605 2 and 3 X12 .909 .617 .317 4.618 2 and 3 3 X13 .821 .585 3.809 4.861 1 and 2 X14 .941 .642 .320 4.620 2 and 3 X15 .955 .624 1.957 4.822 2 and 3 X16 .596 .425 .020 4.602 2 and 3 X18 .044 .044 3.426 4.850 1 and 2

Stepwise Statistics Stepwise Statistics - Wilks' Lambda - November 6, 2018 Wilks' LambdaWilks' Lambda, table, 2 levels of column headers and 1 levels of row headers, table with 10 columns and 6 rows

Number of Exact F Step Lambda df1 df2 df3 Variables Statistic df1 df2 Sig. 1 1 .556 1 2 97 38.758 2 97.000 .000 2 2 .361 2 2 97 31.882 4 192.000 .000 3 3 .247 3 2 97 32.107 6 190.000 .000

Summary of Canonical Discriminant Functions Summary of Canonical Discriminant Functions - Eigenvalues - November 6, 2018

EigenvaluesEigenvalues, table, 1 levels of column headers and 1 levels of row headers, table with 5 columns and 5 rows % of Cumulative Canonical Function Eigenvalue Variance % Correlation 1 1.725a 77.9 77.9 .796 2 .488a 22.1 100.0 .573 a. First 2 canonical discriminant functions were used in the analysis.

Summary of Canonical Discriminant Functions Summary of Canonical Discriminant Functions - Wilks' Lambda - November 6, 2018

Wilks' LambdaWilks' Lambda, table, 1 levels of column headers and 1 levels of row headers, table with 5 columns and 4 rows Test of Wilks' Chi-square df Sig. Function(s) Lambda 1 through 2 .247 134.414 6 .000 2 .672 38.163 2 .000 Analysis 1 Analysis 1 - Standardized Canonical Discriminant Function Coefficients - November 6, 2018

Standardized Canonical Discriminant Function CoefficientsStandardized Canonical Discriminant Function Coefficients, table, 2 levels of column headers and 1 levels of row headers, table with 3 columns and 6 rows Function

1 2 X6 .790 -.141 X11 .867 .232 X17 .655 1.003

Analysis 1 Analysis 1 - Structure Matrix - November 6, 2018

Structure MatrixStructure Matrix, table, 2 levels of column headers and 1 levels of row headers, table with 3 columns and 19 rows Function

1 2 X11 .671* -.213 X6 .589* -.567 X17 -.072 .967* X18b .512 .719* X9b .467 .536* X16b .404 .473* X13b -.067 .348* X12b -.043 .296* X10b .066 .295* X7b .103 .261* X15b .073 .197* X8b -.002 -.195* X14b .039 -.099* Pooled within-groups correlations between discriminating variables and standardized canonical discriminant functions Variables ordered by absolute size of correlation within function. *. Largest absolute correlation between each variable and any discriminant function b. This variable not used in the analysis.

Analysis 1 Analysis 1 - Canonical Discriminant Function Coefficients - November 6, 2018

Canonical Discriminant Function CoefficientsCanonical Discriminant Function Coefficients, table, 2 levels of column headers and 1 levels of row headers, table with 3 columns and 8 rows Function

1 2 X6 .742 -.133 X11 .875 .234 X17 .651 .996 (Constant) -13.880 -4.917 Unstandardized coefficients

Analysis 1 Analysis 1 - Functions at Group Centroids - November 6, 2018

Functions at Group CentroidsFunctions at Group Centroids, table, 2 levels of column headers and 1 levels of row headers, table with 3 columns and 7 rows X1 Function 1 2 1 -1.626 -.508 2 -.006 .938 3 1.583 -.502 Unstandardized canonical discriminant functions evaluated at group means

Classification Statistics Classification Statistics - Classification Processing Summary - November 6, 2018

Classification Processing SummaryClassification Processing Summary, table, 0 levels of column headers and 2 levels of row headers, table with 3 columns and 5 rows Processed 100 Missing or out-of- 0 range group codes Excluded At least one missing 0 discriminating variable Used in Output 100

Classification Statistics Classification Statistics - Prior Probabilities for Groups - November 6, 2018

Prior Probabilities for GroupsPrior Probabilities for Groups, table, 2 levels of column headers and 1 levels of row headers, table with 4 columns and 7 rows

Cases Used in Analysis X1 Prior Unweighted Weighted 1 .333 32 32.000 2 .333 35 35.000 3 .333 33 33.000 Total 1.000 100 100.000 Classification Statistics Classification Statistics - Classification Function Coefficients - November 6, 2018

Classification Function CoefficientsClassification Function Coefficients, table, 2 levels of column headers and 1 levels of row headers, table with 4 columns and 8 rows

X1

1 2 3 X6 11.024 12.035 13.406 X11 9.508 11.265 12.319 X17 13.439 15.934 15.534 (Constant) -91.636 -120.224 -136.143 Fisher's linear discriminant functions

Classification Statistics Classification Statistics - Territorial Map - November 6, 2018

Territorial Map Canonical Discriminant Function 2 -8.0 -6.0 -4.0 - 2.0 .0 2.0 4.0 6.0 8.0 +------+------+------+------+------+------+------+------+ 8.0 +122 22+ I 112 233I I 122 223 I I 112 2 33 I I 122 22 3 I I 112 23 3 I 6.0 + 122 + + + + + 223 + I 112 233 I I 122 223 I I 112 233 I I 122 223 I I 112 233 I 4.0 + + 122 + + + +223 + + I 112 233 I I 122 223 I I 112 233 I I 122 223 I I 112 233 I 2.0 + + + 122+ + + 223 + + + I 112 233 I I 122 223 I I 112 * 233 I I 122 223 I I 112 233 I .0 + + + + 122 + 223 + + + + I 112 233 I I * 1223 * I I 13 I I 13 I I 13 I - 2.0 + + + + 13 + + + + I 13 I I 13 I I 13 I I 13 I I 13 I - 4.0 + + + + 13 + + + + I 13 I I 13 I I 13 I I 13 I I 13 I - 6.0 + + + + 13 + + + + I 13 I I 13 I I 13 I I 13 I I 13 I - 8.0 + 13 + +------+------+------+------+------+------+------+------+ -8.0 -6.0 -4.0 - 2.0 .0 2.0 4.0 6.0 8.0 Canonical Discriminant Functio n 1

Symbols used in territorial map

Symbol Group Label ------

1 1 2 2 3 3 * Indicates a group centroid

Classification Statistics Classification Statistics - Casewise Statistics - November 6, 2018

Casewise StatisticsCasewise Statistics, table, 3 levels of column headers and 2 levels of row headers, table with 13 columns and 207 rows Highest Group P(D>d | G=g) Squared Case Number Actual Group Predicted Mahalanobis P(G=g | D=d) Group p df Distance to Centroid 1 1 1 .165 2 .578 3.601 2 1 1 .165 2 .578 3.601 3 3 3 .761 2 .934 .547 4 1 1 .026 2 1.000 7.328 5 3 3 .689 2 .827 .744 6 3 3 .689 2 .827 .744 Original 7 3 3 .510 2 .991 1.347 8 3 3 .987 2 .888 .026 9 1 1 .276 2 .996 2.573 10 1 1 .763 2 .938 .541 11 2 2 .271 2 .853 2.610 12 1 1 .467 2 .982 1.522 13 1 1 .049 2 .999 6.046 14 1 1 .173 2 .985 3.513 15 3 3 .987 2 .888 .026 16 2 2 .651 2 .568 .858 17 2 2 .991 2 .814 .018 18 1 1 .940 2 .823 .124 19 1 3** .782 2 .928 .492 20 3 3 .867 2 .856 .286 21 1 1 .451 2 .966 1.592 22 2 2 .328 2 .970 2.229 23 3 3 .773 2 .871 .515 24 1 2** .912 2 .804 .185 25 3 3 .762 2 .972 .542 26 1 1 .531 2 .843 1.266 27 2 3** .934 2 .880 .137 28 3 3 .547 2 .943 1.208 29 3 3 .762 2 .972 .542 30 2 2 .041 2 .687 6.395 31 1 1 .770 2 .974 .523 32 3 3 .773 2 .871 .515 33 2 2 .619 2 .545 .959 34 1 3** .284 2 .465 2.518 35 3 3 .876 2 .810 .265 36 2 3** .657 2 .617 .839 37 3 3 .515 2 .988 1.329 38 2 2 .507 2 .903 1.359 39 2 2 .135 2 .989 4.001 40 3 3 .871 2 .873 .276 41 1 1 .512 2 .963 1.340 42 1 1 .924 2 .830 .158 43 2 2 .939 2 .891 .127 44 3 3 .782 2 .956 .493 45 3 3 .901 2 .946 .208 46 3 2** .318 2 .572 2.291 47 1 2** .574 2 .539 1.111 48 3 3 .782 2 .956 .493 49 2 2 .271 2 .767 2.614 50 2 2 .707 2 .925 .694 51 3 3 .515 2 .988 1.329 52 1 1 .451 2 .966 1.592 53 1 1 .464 2 .992 1.536 54 1 1 .259 2 .972 2.698 55 3 2** .318 2 .572 2.291 56 3 3 .927 2 .933 .152 57 3 3 .999 2 .897 .001 58 2 2 .341 2 .904 2.154 59 2 2 .752 2 .633 .569 60 2 2 .367 2 .729 2.007 61 2 2 .135 2 .989 4.001 62 2 2 .552 2 .879 1.188 63 3 3 .237 2 .690 2.877 64 1 1 .426 2 .990 1.704 65 2 2 .507 2 .903 1.359 66 3 2** .358 2 .392 2.054 67 3 3 .927 2 .933 .152 68 1 1 .591 2 .574 1.051 69 3 3 .295 2 .971 2.442 70 2 3** .934 2 .880 .137 71 2 2 .809 2 .927 .424 72 2 3** .804 2 .879 .436 73 2 2 .271 2 .767 2.614 74 2 2 .707 2 .925 .694 75 2 2 .642 2 .933 .886 76 3 3 .999 2 .897 .001 77 2 3** .657 2 .617 .839 78 2 2 .809 2 .927 .424 79 3 3 .672 2 .593 .795 80 1 1 .639 2 .913 .895 81 2 2 .408 2 .926 1.792 82 3 3 .430 2 .835 1.687 83 3 3 .779 2 .813 .498 84 1 1 .592 2 .989 1.049 85 1 1 .560 2 .990 1.160 86 2 1** .155 2 .568 3.725 87 1 1 .544 2 .517 1.216 88 1 2** .409 2 .500 1.787 89 1 1 .512 2 .963 1.340 90 1 1 .591 2 .574 1.051 91 3 3 .779 2 .813 .498 92 2 3** .354 2 .631 2.079 93 1 2** .660 2 .631 .833 94 3 3 .430 2 .835 1.687 95 1 2** .862 2 .889 .297 96 2 3** .885 2 .780 .245 97 2 2 .722 2 .612 .651 98 2 1** .282 2 .825 2.531 99 2 2 .752 2 .633 .569 100 2 3** .354 2 .631 2.079 1 1 1 .266 3 .532 3.955 2 1 1 .266 3 .532 3.955 3 3 3 .898 3 .931 .592 4 1 1 .032 3 1.000 8.828 5 3 3 .264 3 .801 3.980 6 3 3 .264 3 .801 3.980 7 3 3 .530 3 .991 2.208 8 3 3 .552 3 .879 2.101 9 1 1 .284 3 .996 3.798 10 1 1 .902 3 .936 .578 11 2 2 .216 3 .831 4.456 12 1 1 .155 3 .979 5.234 13 1 1 .021 3 .999 9.696 14 1 1 .179 3 .984 4.900 15 3 3 .552 3 .879 2.101 16 2 2 .435 3 .540 2.733 17 2 2 .462 3 .799 2.572 18 1 1 .901 3 .817 .582 Cross-validatedb 19 1 3** .848 3 .948 .805 20 3 3 .355 3 .839 3.251 21 1 1 .633 3 .963 1.717 22 2 2 .325 3 .968 3.469 23 3 3 .551 3 .861 2.105 24 1 2** .749 3 .832 1.218 25 3 3 .868 3 .971 .723 26 1 1 .409 3 .825 2.888 27 2 3** .897 3 .903 .597 28 3 3 .724 3 .940 1.323 29 3 3 .868 3 .971 .723 30 2 2 .053 3 .613 7.683 31 1 1 .851 3 .972 .793 32 3 3 .551 3 .861 2.105 33 2 2 .375 3 .513 3.108 34 1 3** .464 3 .482 2.565 35 3 3 .581 3 .797 1.958 36 2 3** .505 3 .651 2.342 37 3 3 .338 3 .987 3.369 38 2 2 .522 3 .895 2.250 39 2 2 .182 3 .989 4.860 40 3 3 .887 3 .868 .640 41 1 1 .206 3 .957 4.567 42 1 1 .955 3 .826 .327 43 2 2 .760 3 .886 1.170 44 3 3 .906 3 .954 .557 45 3 3 .965 3 .944 .271 46 3 2** .140 3 .651 5.472 47 1 2** .474 3 .572 2.508 48 3 3 .906 3 .954 .557 49 2 2 .305 3 .740 3.626 50 2 2 .330 3 .917 3.429 51 3 3 .338 3 .987 3.369 52 1 1 .633 3 .963 1.717 53 1 1 .596 3 .991 1.887 54 1 1 .292 3 .969 3.731 55 3 2** .140 3 .651 5.472 56 3 3 .800 3 .930 1.004 57 3 3 .817 3 .892 .935 58 2 2 .154 3 .888 5.256 59 2 2 .505 3 .610 2.337 60 2 2 .363 3 .703 3.191 61 2 2 .182 3 .989 4.860 62 2 2 .448 3 .869 2.654 63 3 3 .371 3 .660 3.140 64 1 1 .601 3 .990 1.865 65 2 2 .522 3 .895 2.250 66 3 2** .415 3 .413 2.855 67 3 3 .800 3 .930 1.004 68 1 1 .462 3 .546 2.576 69 3 3 .450 3 .969 2.644 70 2 3** .897 3 .903 .597 71 2 2 .444 3 .922 2.678 72 2 3** .787 3 .904 1.060 73 2 2 .305 3 .740 3.626 74 2 2 .330 3 .917 3.429 75 2 2 .530 3 .928 2.208 76 3 3 .817 3 .892 .935 77 2 3** .505 3 .651 2.342 78 2 2 .444 3 .922 2.678 79 3 3 .678 3 .578 1.518 80 1 1 .784 3 .907 1.072 81 2 2 .292 3 .918 3.731 82 3 3 .597 3 .823 1.885 83 3 3 .893 3 .807 .616 84 1 1 .730 3 .989 1.298 85 1 1 .685 3 .990 1.490 86 2 1** .223 3 .629 4.388 87 1 1 .713 3 .505 1.369 88 1 2** .497 3 .528 2.384 89 1 1 .206 3 .957 4.567 90 1 1 .462 3 .546 2.576 91 3 3 .893 3 .807 .616 92 2 3** .525 3 .658 2.236 93 1 2** .636 3 .660 1.703 94 3 3 .597 3 .823 1.885 95 1 2** .884 3 .909 .655 96 2 3** .898 3 .803 .595 97 2 2 .831 3 .603 .876 98 2 1** .451 3 .853 2.639 99 2 2 .505 3 .610 2.337 100 2 3** .525 3 .658 2.236 For the original data, squared Mahalanobis distance is based on canonical functions. For the cross-validated data, squared Mahalanobis distance is based on observations. **. Misclassified case b. Cross validation is done only for those cases in the analysis. In cross validation, each case is classified by the functions derived from all cases other than that case.

Classification Statistics Classification Statistics - Classification Results - November 6, 2018

a,c Classification Results Classification Results, table, 2 levels of column headers and 3 levels of row headers, table with 7 columns and 18 rows Predicted Group

X1 Membership Total 1 2 3 1 25 5 2 32 Original Count 2 2 25 8 35 3 0 3 30 33 1 78.1 15.6 6.3 100.0 % 2 5.7 71.4 22.9 100.0 3 .0 9.1 90.9 100.0 1 25 5 2 32 Count 2 2 25 8 35 3 0 3 30 33 Cross-validatedb 1 78.1 15.6 6.3 100.0 % 2 5.7 71.4 22.9 100.0 3 .0 9.1 90.9 100.0 a. 80.0% of original grouped cases correctly classified. b. Cross validation is done only for those cases in the analysis. In cross validation, each case is classified by the functions derived from all cases other than that case. c. 80.0% of cross-validated grouped cases correctly classified.

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Created Using: IBM SPSS Statistics 24 Creation Date: Nov 06, 2018 Document Version: Original Saved Date: Nov 06, 2018

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