### Table 3 Identification of the Mutual Fund Principal Components: 1991-1995

1998

"... In PAGE 9: ... Twenty four Morningstar categories 7 (accounting for 85% of the mutual funds in our sample) have only one dominant style, since each category apos;s second principal component explains less than 10% of that category apos;s cross sectional variation. Each of these 24 dominant styles has high correlation with a well defined asset class, as shown in Table3 . This is strong evidence that most mutual funds perform as if they follow a buy-and-hold strategy in well defined mixes of standard asset classes.... In PAGE 10: ...8 - section variation but the third principal component does not. In these 18 principal components, 15 have high correlation with well defined asset classes, as shown in Table3 . There are only three principal components which cannot be easily identified with any asset class mix.... In PAGE 34: ...32 - Table3 (cont.) Note: a) This principal component corresponds to the three ASTRA funds (ASTRA Adj Rate Secs I, I-A, and II), which experienced large losses in Dec 94, Jan 95, and Oct 95.... ..."

### Table 1. Sample of Factors Identified from Principal Components Analysis

2004

"... In PAGE 4: ...igure 3. Sample of the dendrogram from the portal project. ........................................................ 9 Table Page Table1 .... In PAGE 16: ...00. We assigned general names to each of the identified factors (see Table1 ). The categories identified in the factor analysis correspond well to the large ... ..."

### TABLE 4. Principal component analysis eigenvalues of the covariance matrix in Sample 1.

2001

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### TABLE 5. Principal component analysis eigenvalues of the covariance matrix in Sample 2.

2001

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### Table 1. Principal component analysis

"... In PAGE 9: ... 60% of the total variability of the data (Fig. 6, Table1 ). The first principal component accounts for c.... ..."

### Table 3 Satisfaction measure summary statistics and principal components analysis.

"... In PAGE 12: ... Overall, we conclude that our market basket fairly represents the variations in prices across the e-tailers in our study. Sample statistics and construct validation In Table3 , we present that sample means and standard deviations of the satisfaction measures across all nine e-tailers for the entire 11-week period. Table 3 about here The means are all above 8 on a 10-point scale.... In PAGE 12: ... Sample statistics and construct validation In Table 3, we present that sample means and standard deviations of the satisfaction measures across all nine e-tailers for the entire 11-week period. Table3 about here The means are all above 8 on a 10-point scale. Some of this ceiling effect may be due to the selection of respondents from the pool of shoppers who have completed a transaction.... ..."

### Table 4: Principal Component Analysis Test Results for all Programs

2004

"... In PAGE 4: ... However, in all the programs studied static CBO did not show any signiflcant correlation with RDI or RE. Table4 shows the results of the principal component analysis when all of the metrics are taken into consideration. Using the Kaiser criterion to select the number of factors to retain we flnd that the metrics mostly capture three orthogonal dimensions in the sample space formed by all measures.... ..."

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### Table 3. Principal Component Analysis Test Results for all Programs

"... In PAGE 4: ...variances) larger than 1.0. This is the Kaiser criterion [13]. Table3 shows the results of the principal component analysis when all of the metrics are taken into considera- tion. Using the Kaiser criterion to select the number of fac- tors to retain we find that the metrics mostly capture two orthogonal dimensions in the sample space formed by all measures.... ..."

### Table 9 Principal Components Analysis of Study II Data (N = 200)

"... In PAGE 60: ... The analysis was conducted both with and without the MAB Information scale included because this measure was not administered in Study III and it was important to compare analyses based on the same set of paper-and-pencil measures for the two studies. Since the results were highly similar, the solution without MAB Information is presented in Table9 . By removing MAB Information, the same variables could be analyzed in both the Study II and III samples.... In PAGE 65: ... Such an analysis requires the evaluation of correlated components. Accordingly, the varimax rotated principal components matrix reported in Table9 was analyzed by a variant of a procedure described by Schmid and Leiman (1957). The varimax matrix was subjected to an oblique rotation using promax (Hendrickson amp; White, 1964).... ..."

### Table 3: Principal Component Analysis (Component Matrix)

2004

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