大学生创新实践项目统计分析结果

大学生创新实践项目统计分析结果

2010年11月15日

入职适应测量分析

一、 项目分析

一是删除数据不全或不诚实问卷 二是通过项目分析，删除几个题项。 Independent Samples Test Levene's Test for Equality of Variances t-test for Equality o r1 Mean Equal variances assumed F .095 Sig. .759 t 3.855 df 75 Sig. (2-tailed) .000 Difference .86585

Equal variances not assumed r2 Equal variances assumed Equal variances not assumed r3 Equal variances assumed Equal variances not assumed r4 Equal variances assumed Equal variances not assumed r5 Equal variances assumed Equal variances not assumed r6 Equal variances assumed Equal variances not assumed r7 Equal variances assumed Equal variances not assumed r8 Equal variances assumed Equal variances not assumed r9 Equal variances assumed Equal variances not assumed r10 Equal variances assumed Equal variances not assumed r11 Equal variances assumed Equal variances not assumed r12 Equal variances assumed Equal variances not assumed r13 Equal variances assumed Equal variances not assumed r14 Equal variances assumed Equal variances not assumed r15 Equal variances assumed Equal variances not assumed r16 Equal variances assumed Equal variances not assumed r17 Equal variances assumed Equal variances not assumed r18 Equal variances assumed 11.271 .001 3.847 2.647 2.576 .361 2.618 2.627 .444 3.672 3.656 .042 4.972 4.910 .024 4.583 4.459 .014 2.431 2.403 .617 1.556 1.558 .009 3.473 3.375 .000 4.801 4.645 .087 -1.932 -1.956 .171 3.028 3.087 .061 .356 .362 .949 3.915 3.937 .329 -.116 -.116 .252 1.966 1.971 .833 3.426 3.397 .003 1.759 73.039 75 58.526 75 74.534 75 72.119 75 67.993 75 58.233 75 68.540 75 74.087 75 57.392 75 54.252 75 74.684 75 73.063 75 73.235 75 74.858 75 73.340 75 74.322 75 70.302 75 .000 .010 .013 .011 .010 .000 .000 .000 .000 .000 .000 .017 .019 .124 .124 .001 .001 .000 .000 .057 .054 .003 .003 .723 .718 .000 .000 .908 .908 .053 .052 .001 .001 .083 .86585 .55488 .55488 .55352 .55352 .71070 .71070 .97222 .97222 1.01084 1.01084 .57656 .57656 .36721 .36721 .76423 .76423 .99661 .99661 -.49932 -.49932 .72629 .72629 .09011 .09011 .89160 .89160 -.02033 -.02033 .40041 .40041 .81843 .81843 .33266 .845 .591 4.267 5.327 6.277 .253 7.102 16.348 3.008 1.914 3.618 .004 .966 1.334 .045 9.670

Equal variances not assumed r19 Equal variances assumed Equal variances not assumed r20 Equal variances assumed Equal variances not assumed 1.291 .260 1.720 1.277 1.280 .277 4.490 4.425 61.589 75 74.292 75 66.891 .090 .205 .204 .000 .000 .33266 .28862 .28862 .73442 .73442 1.199

删除题目8、11、13、15、16、18、19（红字部分）

二、能否进行因子分析检验？

KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity Approx. Chi-Square df Sig. .558 197.458 78 .000

Total Variance Explained Component 1 2 Total 2.152 1.792 Initial Eigenvalues % of Variance 16.552 13.783 Cumulative % 16.552 30.335 Extraction Sums of Squared Loadings Total 2.152 1.792 % of Variance 16.552 13.783 Cumulative % 16.552 30.335 RotTotal 1.81.8

3 4 5 6 7 8 9 10 11 12 13 1.287 1.233 1.092 .968 .931 .819 .748 .600 .538 .467 .375 9.899 9.481 8.400 7.443 7.165 6.297 5.750 4.612 4.138 3.592 2.886 40.233 49.714 58.115 65.558 72.723 79.020 84.770 89.383 93.521 97.114 100.000 1.287 1.233 1.092 9.899 9.481 8.400 40.233 49.714 58.115 1.31.31.1 Extraction Method: Principal Component Analysis.

Rotated Component Matrix a r9 r5 r20 r3 r12 r14 r10 r7 r2 r4 r1 r17 r6 1 .823 .790 .493 -.290 .048 .420 .072 -.025 -.168 .084 .152 -.043 .054 2 -.067 .040 .029 .719 .712 .650 .607 .074 -.066 .104 .109 .063 -.009 Component 3 .005 .142 -.269 -.077 .040 .039 .467 .786 .175 -.271 .121 -.201 .473 4 .023 .067 .038 .041 .236 -.154 .032 .075 .737 .707 .417 -.013 .027 5 .109 .018 -.177 .073 .153 -.245 -.048 -.042 -.124 .114 .018 .764 .664 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 5 iterations.

第5因子题项只有两项r17和r6，层面所涵盖的题项内容太少，将之删除似乎较为

适宜。因为这是一个探索性因子分析，题项删除后因子结构也会随之改变，因而必须再进行一次因子分析，以验证量表的结构效度。 Rotated Component Matrix a r9 r5 r20 r3 r12 r10 r14 r2 r4 r1 r7 1 .813 .776 .524 -.278 .049 .049 .432 -.158 .109 .150 -.073 Component 2 -.051 .040 .008 .741 .722 .616 .615 -.041 .143 .071 .059 3 .025 .063 -.005 .022 .233 .012 -.200 .721 .710 .418 .078 4 -.022 .177 -.183 -.161 .036 .447 .155 .161 -.322 .265 .841 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 5 iterations.

再一次因子分析后第4因子只有一个题项。删除。 Total Variance Explained Component 1 2 3 4 5 6 7 8 9 10 Total 2.091 1.744 1.256 .973 .911 .830 .696 .589 .503 .406 Initial Eigenvalues % of Variance 20.914 17.437 12.555 9.734 9.113 8.301 6.960 5.891 5.032 4.063

Cumulative % 20.914 38.351 50.906 60.640 69.753 78.054 85.014 90.905 95.937 100.000 Extraction Sums of Squared Loadings Total 2.091 1.744 1.256 % of Variance 20.914 17.437 12.555 Cumulative % 20.914 38.351 50.906 RotaTotal 1.91.81.3

Total Variance Explained Component 1 2 3 Total 2.091 1.744 1.256 Initial Eigenvalues % of Variance 20.914 17.437 12.555 Cumulative % 20.914 38.351 50.906 Extraction Sums of Squared Loadings Total 2.091 1.744 1.256 % of Variance 20.914 17.437 12.555 Cumulative % 20.914 38.351 50.906 RotaTotal 1.91.81.34 .973 9.734 60.640 5 .911 9.113 69.753 6 .830 8.301 78.054 7 .696 6.960 85.014 8 .589 5.891 90.905 9 .503 5.032 95.937 Extraction Method: Principal Component Analysis. Rotated Component Matrixa Component 1 2 3 r11 .706 .043 .026 r12 .704 .011 .265 r14 .665 .409 -.169 R15 .663 -.321 .058 R19 -.025 .811 .038 R17 .109 .780 .073 r20 -.044 .520 .012 r4 .025 .078 .729 r2 -.027 -.158 .710 r1 .144 .149 .413 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 4 iterations.

三、信度检验

因子1：人际适应 Reliability Statistics Cronbach's Alpha .731 N of Items 4

因子2：文化适应

Reliability Statistics Cronbach's Alpha .790 N of Items 3

因子3：能力适应 Reliability Statistics Cronbach's Alpha .796 N of Items 3

影响因素分析

Independent Samples Test y1 Equal variances assumed Equal variances not assumed Levene's Test for Equality of Variances t-tF .157 Sig. .693 t 1.849 1.849 df 80 78.515 80 80.000 80 73.278 80 79.999 80 69.381 80 74.111 80 73.541 80 78.282 80 79.689 80 79.866 80 77.044 Sig. (2-tailed) .068 .068 .627 .627 .322 .323 .339 .339 .001 .001 .018 .018 .001 .001 .031 .031 .766 .766 .030 .030 .065 .065 Me .215 .644 y2 Equal variances assumed Equal variances not assumed -.488 -.488 6.073 .016 y3 Equal variances assumed Equal variances not assumed .996 .996 .007 .934 y4 Equal variances assumed Equal variances not assumed .963 .963 1.543 .218 y5 Equal variances assumed Equal variances not assumed 3.515 3.515 6.594 .012 y6 Equal variances assumed Equal variances not assumed 2.422 2.422 .856 .358 y7 Equal variances assumed Equal variances not assumed 3.371 3.371 1.619 .207 y8 Equal variances assumed Equal variances not assumed 2.191 2.191 .509 .478 y9 Equal variances assumed Equal variances not assumed -.299 -.299 .415 .521 y10 Equal variances assumed Equal variances not assumed 2.204 2.204 4.420 .039 y11 Equal variances assumed Equal variances not assumed 1.873 1.873

y12 Equal variances assumed Equal variances not assumed .000 .984 .818 .818 80 79.887 80 78.008 80 72.526 80 79.896 80 79.169 80 74.296 80 76.585 80 78.655 80 71.985 80 78.771 80 79.610 80 78.281 .416 .416 .013 .013 .000 .000 .006 .006 .045 .045 .001 .001 .000 .000 .001 .001 .000 .000 .021 .021 .034 .035 .000 .000 2.556 .114 y13 Equal variances assumed Equal variances not assumed 2.555 2.555 8.254 .005 y14 Equal variances assumed Equal variances not assumed 6.221 6.221 .004 .950 y15 Equal variances assumed Equal variances not assumed 2.826 2.826 .110 .741 y16 Equal variances assumed Equal variances not assumed 2.033 2.033 4.428 .039 y17 Equal variances assumed Equal variances not assumed 3.339 3.339 .718 .399 y18 Equal variances assumed Equal variances not assumed 4.574 4.574 .915 .342 y19 Equal variances assumed Equal variances not assumed 3.481 3.481 9.233 .003 y20 Equal variances assumed Equal variances not assumed 5.118 5.118 1.909 .171 y21 Equal variances assumed Equal variances not assumed 2.362 2.362 .436 .511 y22 Equal variances assumed Equal variances not assumed 2.151 2.151 1.957 .166 y23 Equal variances assumed Equal variances not assumed 3.997 3.997 Rotated Component Matrix a y14 y19 y23 y17 y13 y16 1 .673 .663 .649 .522 .420 -.053 2 -.101 .291 -.136 .019 -.372 .772 3 .250 .047 -.103 -.137 -.062 .141 4 .065 -.295 .062 .156 .195 -.040 Component 5 .201 -.089 -.012 -.091 -.063 -.008 6 .077 -.210 .020 .188 .214 -.058 7 .034 .137 -.037 -.220 .142 -.016 8 .107 -.181 .034 -.027 -.087 -.051 9 .052 -.029 -.047 .005 .029 .043 y4 y9 y6 y7 y20 y15 y11 y21 y3 y22 y2 y8 y12 y18 y10 y5 y1 -.005 -.010 .025 .068 .220 .056 -.155 -.147 .035 .110 -.130 .020 -.266 .410 -.106 .139 .053 -.576 -.156 -.079 .049 .046 -.014 .403 .217 -.198 .111 -.061 .048 -.102 .110 -.217 .231 -.042 .133 -.766 .630 .014 .207 .231 -.187 .367 .225 -.170 .156 .008 .104 -.037 .042 -.098 -.067 -.255 .143 .260 .824 .454 -.092 .251 .000 .064 .138 .423 .048 .111 -.155 -.016 -.084 -.023 -.034 .035 .168 .046 -.236 .784 .586 -.426 .014 -.276 -.247 -.048 -.109 .112 -.095 .221 -.043 -.094 .023 .030 .103 -.181 -.024 .004 .299 .690 .625 -.483 .062 .010 -.068 -.139 .157 .001 -.133 .056 .085 .023 .294 -.130 .256 .044 .172 -.353 -.265 .868 -.061 .095 .162 -.301 -.087 -.053 -.192 -.116 -.035 .174 .000 -.024 .035 -.167 .183 .021 .014 .800 .731 -.095 .095 .018 .154 .065 .021 -.027 -.046 .107 -.113 .068 -.145 .045 -.206 -.009 -.082 .071 .833 .706 -.023 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 18 iterations.

去掉y1和y8

Rotated Component Matrix a y14 y23 y19 y17 y13 y16 y4 y9 1 .673 .664 .657 .469 .433 -.063 .007 .014 2 -.090 -.139 .257 .075 -.308 .725 -.668 -.127 3 .263 -.106 .075 -.188 -.041 .169 .091 -.751 Component 4 .067 .074 -.254 .048 .222 -.079 -.182 .122

5 .166 -.031 -.100 -.008 -.002 -.120 -.082 .084 6 .085 .018 -.278 .325 .255 -.154 -.131 .030 7 .089 .039 -.238 .002 -.177 -.032 .000 -.183 8 .094 .008 -.054 -.026 -.029 .129 .156 .105

y6 y7 y20 y2 y15 y11 y21 y3 y22 y12 y18 y5 y10 .013 .056 .261 -.175 .046 -.141 -.128 .033 .104 -.238 .454 .112 -.123 -.087 .141 .030 -.047 .004 .506 .143 -.108 .111 -.097 .091 .159 -.302 .631 -.020 .211 .023 .290 -.074 .357 .268 -.221 .088 .021 -.086 .040 .271 .781 .568 .450 -.158 .180 .039 -.007 .020 .134 -.112 -.161 .067 .121 .093 -.241 -.128 .701 .593 -.559 .009 -.372 -.079 .081 .105 -.067 .065 .233 -.221 -.305 .000 .023 .164 .716 .612 .024 -.159 .093 -.192 -.099 -.032 .108 .078 .049 -.061 .033 -.199 .273 .796 .670 .124 -.195 .032 .004 -.051 -.287 .219 -.037 .114 -.150 .171 -.105 .105 .792 .697 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 19 iterations. Descriptive Statistics sex y1 y2 y3 y4 y5 rsum Valid N (listwise) N 132 132 132 132 132 132 132 132 Minimum .00 2.20 2.20 1.83 1.67 1.50 2.25 Maximum 1.00 4.00 4.20 3.83 5.00 5.00 4.25 Mean .6515 3.1773 3.2303 2.9353 3.4795 3.1023 3.1908 Std. Deviation .47831 .37693 .39345 .43687 .70977 .62085 .32405

Correlations sex Pearson Correlation Sig. (2-tailed) sex 1 y1 .151 .085 y2 -.025 .780 y3 -.011 .902 y4 .196 .024 *y5 .037 .670 rsum .133 .129

N y1 Pearson Correlation Sig. (2-tailed) N y2 Pearson Correlation Sig. (2-tailed) N y3 Pearson Correlation Sig. (2-tailed) N y4 Pearson Correlation Sig. (2-tailed) N y5 Pearson Correlation Sig. (2-tailed) N rsum Pearson Correlation Sig. (2-tailed) N 132 .151 .085 132 -.025 .780 132 -.011 .902 132 .196 .024 132 .037 .670 132 .133 .129 132 *132 1 132 .001 .995 132 -.021 .808 132 .024 .786 132 -.039 .657 132 -.056 .520 132 .236 .006 **132 .155 .076 132 .061 .490 132 .042 .634 132 .181 .038 *132 -.053 .542 132 -.101 .247 132 -.178 .041 132 .087 .324 132 .204 .019 **132 .001 .995 132 -.021 .808 132 -.039 .657 132 .155 .076 132 -.053 .542 132 132 1 132 .024 .786 132 -.056 .520 132 .061 .490 132 -.101 .247 132 132 1 132 .236 .006 132 .042 .634 132 -.178 .041 132 ***132 1 132 .181 .038 132 .087 .324 132 *132 1 132 .204 .019 132 *132 1 132 *. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed). Coefficients Standardized Unstandardized Coefficients Model 1 (Constant) y5 2 (Constant) y5 y3 3 (Constant) y5 B 2.861 .106 3.255 .110 -.139 3.691 .115

Std. Error .142 .045 .227 .044 .063 .392 .045 .220 .211 -.187 .204 Coefficients Beta t 20.181 2.371 14.352 2.496 -2.205 9.419 2.528 Sig. .000 .019 .000 .014 .029 .000 .013 .935 .998 .998 1.000 Collinearity Statistics Tolerance VIF a 1.001.001.00 1.06y3 sex y1 y2 y4 a. Dependent Variable: rsum -.148 .084 -.093 -.085 .027 .064 .059 .074 .070 .041 -.200 .124 -.108 -.103 .060 -2.304 1.430 -1.252 -1.225 .659 .023 .155 .213 .223 .511 .939 .933 .945 .990 .865 1.061.071.051.011.15

以上是朱洁琴的部分。 Descriptive Statistics r1 r2 r3 jx Valid N (listwise) N 132 132 132 132 132 Minimum 2.00 2.00 1.33 2.50 Maximum 4.00 4.67 5.00 4.08 Mean 3.1667 3.0908 3.3155 3.1725 Std. Deviation .41290 .62442 .65145 .36961 Coefficients Standardized Unstandardized Coefficients Model 1 (Constant) r2 2 (Constant) r2 r1 a. Dependent Variable: jx B 2.262 .295 1.661 .306 .179 Std. Error .142 .045 .264 .044 .067 .516 .200 .498 Coefficients Beta t 15.933 6.540 6.295 6.915 2.681 Sig. .000 .000 .000 .000 .008 .991 .991 1.000 Collinearity Statistics Tolerance VIF a 1.001.001.00

Excluded Variables Collinearity Statistics Partial Model 1 r1 r3 2 r3 Beta In .200 -.088 -.089 baacMinimum Tolerance .991 1.000 1.000 VIF 1.009 1.000 1.000 Tolerance .991 1.000 .991 t 2.681 -1.155 -1.197 Sig. .008 .250 .234 Correlation .230 -.101 -.105 a. Predictors in the Model: (Constant), r2 b. Predictors in the Model: (Constant), r2, r1 c. Dependent Variable: jx

以上樊晨龙部分。

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