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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_factor_analysis.wasp

Title produced by software

Factor Analysis

Date of computation

Fri, 23 Nov 2018 03:32:41 +0100

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2018/Nov/23/t1542940453ndbaap3fb75wz1b.htm/, Retrieved Mon, 29 Apr 2024 08:17:57 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=315696, Retrieved Mon, 29 Apr 2024 08:17:57 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

races

Estimated Impact

115

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Factor Analysis] [races] [2018-11-23 02:32:41] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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Dataseries X:

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Histogram

Boxplots

Runners	Distance	Handicap	Class	Stake>5k	Odds>2	Win
[1]	11	7	0	5	0	1	0
[2]	5	8	0	3	0	0	1
[3]	7	5	1	2	1	1	0
[4]	4	8	0	1	1	0	1
[5]	8	14	1	4	0	1	1
[6]	10	10	1	3	1	0	0
[7]	6	8	0	4	0	0	1
[8]	4	6	0	3	0	0	0
[9]	13	8	1	3	1	1	0
[10]	9	14	1	1	1	1	0
[11]	12	7	0	3	1	1	0
[12]	5	13	0	4	0	0	1
[13]	12	5	1	4	1	1	1
[14]	4	14	0	1	1	0	1
[15]	12	7	1	2	1	1	0
[16]	18	6	1	3	1	1	1
[17]	9	8	0	1	1	1	1
[18]	22	10	1	5	0	1	0
[19]	10	9	1	5	0	1	0
[20]	5	7	0	4	0	0	1
[21]	16	6	0	5	0	1	1
[22]	12	10	0	6	0	0	0
[23]	3	6	0	2	1	0	1
[24]	12	8	1	3	1	1	0
[25]	3	18	0	3	1	0	1
[26]	18	6	1	5	0	1	0
[27]	4	12	0	6	0	0	0
[28]	6	6	1	5	0	0	1
[29]	8	7	0	7	0	0	1
[30]	12	7	0	6	0	1	1
[31]	16	10	1	6	0	1	0
[32]	10	12	1	5	0	0	1
[33]	16	9	0	5	1	1	0
[34]	16	8	0	5	1	1	0
[35]	14	14	1	3	1	1	1
[36]	18	6	1	2	1	1	0
[37]	24	8	1	4	1	1	0
[38]	6	11	0	4	1	0	0
[39]	11	7	0	4	1	1	0
[40]	6	6	1	5	0	0	1
[41]	13	8	0	6	0	1	1
[42]	12	7	0	4	1	1	1
[43]	4	6	0	2	1	0	1
[44]	12	7	1	3	1	0	1
[45]	3	14	0	3	1	0	1
[46]	12	7	0	4	1	0	1
[47]	18	8	1	6	0	1	0
[48]	24	7	1	4	1	1	0
[49]	6	6	0	4	1	0	1
[50]	9	9	0	1	1	1	1
[51]	9	12	1	2	1	1	0
[52]	15	8	1	3	1	1	0
[53]	8	8	0	4	1	0	1
[54]	22	11	1	5	1	1	0
[55]	9	7	0	5	0	0	1
[56]	9	6	1	4	0	1	1
[57]	4	10	1	2	1	0	1
[58]	4	9	0	1	1	0	1
[59]	6	9	0	4	0	0	1
[60]	17	7	1	5	0	1	1
[61]	17	5	0	4	0	1	1
[62]	17	8	0	5	0	1	1
[63]	7	6	0	4	1	1	1
[64]	22	6	0	6	0	1	1
[65]	19	12	1	4	0	1	1
[66]	24	6	1	7	0	1	0
[67]	10	11	1	5	0	1	1
[68]	9	12	1	2	1	1	0
[69]	3	8	0	2	1	0	1
[70]	12	7	0	4	0	1	1
[71]	13	6	0	1	1	1	0
[72]	16	7	1	3	1	1	0
[73]	12	5	1	3	1	1	0
[74]	8	6	0	4	0	0	1
[75]	7	9	0	4	0	0	1
[76]	9	5	1	3	1	1	0
[77]	10	10	1	4	0	1	1
[78]	7	12	0	1	1	1	1
[79]	12	12	1	3	1	1	0
[80]	15	9	1	4	0	1	0
[81]	18	8	0	6	0	1	1
[82]	9	8	0	4	0	1	1
[83]	12	7	0	6	0	0	1
[84]	18	8	1	4	1	1	0
[85]	18	12	1	4	1	1	0
[86]	14	6	0	4	0	0	0
[87]	24	5	1	6	0	1	1
[88]	11	7	0	6	0	1	0
[89]	14	5	0	5	0	1	1
[90]	18	8	1	6	0	1	0
[91]	16	8	1	3	1	1	0
[92]	12	12	0	4	0	0	1
[93]	15	13	1	5	0	1	0
[94]	16	6	0	4	0	1	0
[95]	18	6	1	4	0	1	1
[96]	7	5	1	4	0	1	0
[97]	18	5	1	6	0	1	1
[98]	8	9	0	4	0	0	1
[99]	10	9	1	3	1	1	1
[100]	11	9	0	6	0	1	0
[101]	18	12	1	6	0	1	0
[102]	5	7	0	3	1	1	1
[103]	15	7	1	2	1	1	1
[104]	21	6	1	2	1	1	0
[105]	19	6	0	2	1	0	0
[106]	9	15	0	1	1	0	0
[107]	10	15	1	2	1	1	0
[108]	10	11	0	4	0	1	1
[109]	19	6	0	4	0	1	0
[110]	18	8	1	4	0	1	0
[111]	6	7	0	3	0	0	0
[112]	7	7	0	3	0	0	1
[113]	6	6	0	1	1	0	0
[114]	18	12	1	4	0	1	1
[115]	12	15	1	5	0	0	0
[116]	8	5	0	1	1	1	0
[117]	16	8	1	2	1	1	0
[118]	6	8	0	1	1	1	1
[119]	6	18	0	1	1	0	1
[120]	10	8	0	1	1	1	1
[121]	14	7	0	1	1	1	0
[122]	22	7	1	3	1	1	0
[123]	11	7	0	4	0	0	1
[124]	10	7	0	4	0	0	1
[125]	18	10	1	4	0	1	0
[126]	3	10	0	3	1	0	1
[127]	20	5	1	5	0	1	0
[128]	20	8	0	6	0	1	1
[129]	19	7	1	6	0	1	0
[130]	5	8	0	3	1	0	0
[131]	5	11	0	2	1	1	0
[132]	6	12	0	1	1	1	0
[133]	8	7	0	1	1	1	1
[134]	17	12	1	3	1	1	0
[135]	16	8	0	4	0	1	1
[136]	20	5	1	4	0	1	0
[137]	19	8	1	5	0	1	0
[138]	11	7	1	4	0	1	1
[139]	3	8	0	1	1	0	0
[140]	14	9	1	3	1	1	0
[141]	7	7	0	3	1	1	1
[142]	19	8	1	5	0	1	1
[143]	11	6	0	4	0	0	1
[144]	8	12	0	4	0	0	1
[145]	6	6	0	3	1	0	1
[146]	21	8	1	3	1	1	0
[147]	12	8	1	2	1	1	1
[148]	9	15	0	1	1	1	1
[149]	20	11	1	3	1	1	0
[150]	13	5	0	1	1	1	0
[151]	22	6	1	4	1	1	1
[152]	9	7	1	2	1	1	1
[153]	4	10	0	1	1	0	1
[154]	22	6	1	3	1	1	0
[155]	8	16	1	3	1	1	0
[156]	4	8	0	4	0	0	1
[157]	11	10	0	4	0	1	1
[158]	10	5	0	5	0	0	1
[159]	6	8	0	5	0	0	1
[160]	16	12	1	5	1	1	1
[161]	17	5	1	5	0	1	0
[162]	17	16	1	5	0	1	0
[163]	14	7	1	6	0	1	0
[164]	14	7	1	6	0	1	0
[165]	13	8	0	4	0	0	1
[166]	12	6	0	4	0	0	0
[167]	11	6	0	4	0	0	0
[168]	20	6	1	5	0	1	0
[169]	19	6	0	5	0	1	1
[170]	18	16	1	6	0	1	1
[171]	16	10	0	6	0	1	1
[172]	14	11	0	4	0	1	1
[173]	12	12	0	6	0	1	1
[174]	6	10	0	1	1	0	0
[175]	5	6	0	4	0	1	0
[176]	19	5	1	3	1	1	1
[177]	20	7	0	7	0	1	0
[178]	11	7	0	4	0	1	1
[179]	14	5	0	5	0	0	0
[180]	13	10	0	4	0	1	1
[181]	7	8	0	3	0	0	0
[182]	11	7	0	4	0	1	1
[183]	14	8	1	4	0	1	0
[184]	12	5	1	4	0	1	0
[185]	19	10	1	5	0	1	0
[186]	4	7	0	4	0	0	0
[187]	20	5	0	5	0	1	0
[188]	16	7	1	4	0	1	0
[189]	10	8	0	4	0	0	1
[190]	12	8	1	4	0	1	0
[191]	14	5	0	5	0	1	1
[192]	18	14	1	5	0	1	1
[193]	11	8	0	5	0	0	1
[194]	15	8	0	4	0	1	1
[195]	17	8	1	6	0	1	0
[196]	11	8	0	5	0	0	1
[197]	19	9	1	6	0	1	1
[198]	20	5	0	4	0	1	0
[199]	18	5	0	4	0	0	0
[200]	15	12	1	5	0	1	1
[201]	17	10	0	7	0	1	0
[202]	17	10	1	3	1	1	0
[203]	7	6	0	3	1	0	0
[204]	15	6	0	4	0	0	1
[205]	20	7	1	7	0	1	0
[206]	18	7	0	4	0	1	0
[207]	18	8	1	4	0	1	0
[208]	23	7	0	4	1	0	1
[209]	13	8	0	1	1	1	0
[210]	7	11	0	1	1	0	0
[211]	12	5	0	1	1	1	0
[212]	11	16	1	2	1	1	0
[213]	16	10	1	4	1	1	0
[214]	17	8	0	5	0	1	1
[215]	20	11	0	5	0	1	0
[216]	12	5	0	1	1	1	1
[217]	27	5	1	4	1	1	0
[218]	7	15	1	3	1	0	0
[219]	7	7	0	4	0	0	0
[220]	15	6	0	5	0	1	0
[221]	8	6	0	3	0	1	0
[222]	20	6	1	6	0	1	0
[223]	6	18	1	3	1	1	1
[224]	13	8	0	4	0	0	0
[225]	20	8	0	5	0	1	1
[226]	20	8	1	6	0	1	0
[227]	20	6	1	6	0	1	0
[228]	3	8	0	4	0	0	1
[229]	10	6	0	1	1	1	0
[230]	29	6	1	2	1	1	1
[231]	6	11	0	1	1	1	0
[232]	29	6	1	2	1	1	0
[233]	20	8	1	3	1	1	0
[234]	7	13	1	3	1	1	0
[235]	13	5	1	3	1	1	1
[236]	6	6	0	1	1	1	0
[237]	20	10	1	2	1	1	0
[238]	20	14	1	3	1	1	0
[239]	20	8	1	3	1	1	0
[240]	23	6	0	4	0	1	0
[241]	12	6	0	4	0	1	0
[242]	13	14	0	7	0	1	1
[243]	14	12	1	4	0	1	0
[244]	18	7	1	6	0	1	0
[245]	11	7	0	4	0	0	1
[246]	18	16	1	6	0	1	0
[247]	18	7	1	5	0	1	0
[248]	14	12	0	7	0	1	1
[249]	9	5	0	3	0	1	1
[250]	14	5	0	5	0	1	1
[251]	17	8	1	5	0	1	0
[252]	16	9	1	4	0	1	0
[253]	19	10	1	6	0	1	1
[254]	19	10	1	6	0	1	0
[255]	14	7	0	4	0	1	0
[256]	17	7	0	4	0	0	1
[257]	13	6	0	5	0	1	1
[258]	13	6	0	5	0	1	1
[259]	10	8	1	3	1	1	1
[260]	13	8	0	6	0	1	1
[261]	20	11	1	6	0	1	0
[262]	10	16	1	6	0	1	1
[263]	12	12	1	5	0	1	1
[264]	8	8	0	4	0	0	1
[265]	9	7	0	3	0	1	0
[266]	5	10	0	1	1	0	1
[267]	20	5	1	5	0	1	0
[268]	22	8	1	5	0	1	0
[269]	20	10	1	4	0	1	0
[270]	7	7	0	4	0	0	1
[271]	11	6	0	4	0	1	0
[272]	10	7	1	4	0	1	0
[273]	13	16	1	4	1	1	1
[274]	4	8	0	3	1	0	1
[275]	13	5	1	4	0	1	0
[276]	16	16	1	5	0	1	0
[277]	18	7	1	4	0	1	0
[278]	6	8	0	3	1	0	1
[279]	8	7	0	1	1	1	1
[280]	4	6	0	4	0	0	1
[281]	11	8	1	4	0	1	1
[282]	6	10	0	4	0	1	1
[283]	13	6	0	4	0	1	1
[284]	7	8	1	5	0	0	0
[285]	11	10	1	3	1	1	0
[286]	9	8	0	4	0	1	1
[287]	18	5	1	5	0	1	0
[288]	9	10	0	5	0	1	0
[289]	7	11	0	4	0	0	1
[290]	13	6	1	4	0	1	1
[291]	11	12	1	3	1	1	0
[292]	3	14	0	3	1	0	1
[293]	11	7	0	4	0	1	0
[294]	11	8	1	4	0	1	0
[295]	15	5	0	6	0	1	1
[296]	9	5	1	4	0	0	0
[297]	16	6	0	6	0	0	0
[298]	10	16	1	5	0	0	0
[299]	16	7	1	5	0	1	1
[300]	8	12	0	5	0	1	0
[301]	9	10	0	4	0	0	1
[302]	5	9	0	4	0	0	1
[303]	23	6	1	5	0	1	0
[304]	17	10	1	7	0	1	0
[305]	7	14	1	3	0	1	0
[306]	14	7	0	4	0	0	1
[307]	10	6	0	4	0	0	0
[308]	19	5	1	5	0	1	0
[309]	9	12	0	1	1	1	0
[310]	9	6	0	1	1	1	0
[311]	7	8	0	1	1	1	1
[312]	26	7	1	2	1	1	0
[313]	8	7	0	2	1	1	1
[314]	17	8	1	1	1	1	0
[315]	17	16	1	3	1	1	0
[316]	11	7	1	3	1	1	1
[317]	7	8	0	4	0	0	1
[318]	8	14	1	4	1	0	1
[319]	8	11	1	3	1	1	0
[320]	20	5	1	3	1	1	0
[321]	10	7	0	4	0	0	1
[322]	18	8	1	7	0	0	1
[323]	10	8	0	4	0	0	1
[324]	16	14	1	5	0	1	0
[325]	5	10	0	3	1	0	0
[326]	20	6	1	2	1	1	0
[327]	16	6	0	4	0	0	1
[328]	14	6	0	4	0	0	1
[329]	14	8	0	4	0	0	1
[330]	13	8	0	4	0	0	1
[331]	6	6	0	3	0	0	1
[332]	12	6	1	2	1	1	0
[333]	4	7	0	4	0	0	0
[334]	20	14	1	6	0	1	0
[335]	18	10	1	6	0	1	0
[336]	13	7	0	6	0	0	0
[337]	7	10	0	4	0	0	0
[338]	12	7	0	6	0	1	1
[339]	20	8	1	5	0	1	0
[340]	14	6	0	4	0	0	1
[341]	10	16	1	4	0	1	0
[342]	4	7	0	4	1	0	1
[343]	18	5	1	4	0	1	0
[344]	9	7	0	4	0	0	1
[345]	12	5	0	7	0	1	0
[346]	14	6	1	5	0	1	1
[347]	11	8	0	6	0	1	0
[348]	13	8	0	4	0	0	0
[349]	14	12	1	5	0	1	0
[350]	20	10	1	6	0	1	0
[351]	16	12	0	5	0	1	0
[352]	16	5	1	3	1	1	1
[353]	6	8	0	1	1	1	0
[354]	7	6	0	1	1	0	1
[355]	6	5	1	1	1	0	1
[356]	27	7	0	4	1	1	1
[357]	24	5	1	4	1	1	0
[358]	8	12	0	1	1	1	1
[359]	12	7	1	2	1	1	1
[360]	5	7	0	1	1	0	1
[361]	14	10	1	3	1	1	1
[362]	8	6	1	2	1	1	1
[363]	5	8	0	3	1	0	1
[364]	13	12	0	7	0	1	0
[365]	13	5	0	4	0	1	1
[366]	18	6	0	4	0	0	0
[367]	20	6	0	6	0	1	0
[368]	18	7	1	5	0	1	0
[369]	18	7	1	5	0	1	0
[370]	6	13	0	5	0	1	12.25406445291434	9.1	-0.15490195998574	1.43136376415899	2.25527250510331	4	4	4
'B.bat'	-1.69897000433602	-0.52287874528034	15.8	0.5910646070265	1.27875360095283	1.54406804435028	1	1	1
'Tapir'	2.20411998265592	2.22788670461367	5.2	0	1.48287358360875	2.59328606702046	4	5	4
'Cat'	0.51851393987789	1.40823996531185	10.9	0.55630250076729	1.44715803134222	1.79934054945358	1	2	1
'Chimp'	1.71733758272386	2.64345267648619	8.3	0.14612803567824	1.69897000433602	2.36172783601759	1	1	1
'Chinchilla'	-0.36653154442041	0.80617997398389	11	0.17609125905568	0.84509804001426	2.04921802267018	5	4	4
'Cow'	2.66745295288995	2.62634036737504	3.2	-0.15490195998574	1.47712125471966	2.44870631990508	5	5	5
'Mole'	-1.09691001300806	0.079181246047625	6.3	0.32221929473392	0.54406804435028	1.6232492903979	1	1	1
'Hedgehog'	-0.10237290870956	0.54406804435028	6.6	0.61278385671974	0.77815125038364	1.6232492903979	2	2	2
'Galago'	-0.69897000433602	0.69897000433602	9.5	0.079181246047625	1.01703333929878	2.07918124604762	2	2	2
'Goat'	1.44185217577329	2.06069784035361	3.3	-0.30102999566398	1.30102999566398	2.17026171539496	5	5	5
'Hamster'	-0.92081875395238	0	11	0.53147891704226	0.5910646070265	1.20411998265592	3	1	2
'Seal'	1.92941892571429	2.51188336097887	4.7	0.17609125905568	1.61278385671974	2.49136169383427	1	3	1
'Squirrel'	-1	0.60205999132796	10.4	0.53147891704226	0.95424250943932	1.44715803134222	5	1	3
'Guinea_pig'	0.01703333929878	0.74036268949424	7.4	-0.096910013008056	0.88081359228079	1.83250891270624	5	3	4
'Horse'	2.71683772329952	2.81624129999178	2.1	-0.096910013008056	1.66275783168157	2.52633927738984	5	5	5
'L.bat'	-2	-0.60205999132796	17.9	0.30102999566398	1.38021124171161	1.69897000433602	1	1	1
'Man'	1.79239168949825	3.12057393120585	6.1	0.27875360095283	2	2.42651126136458	1	1	1
'Mouse'	-1.69897000433602	-0.39794000867204	11.9	0.11394335230684	0.50514997831991	1.27875360095283	4	1	3
'N.opossum'	0.23044892137827	0.79934054945358	13.8	0.7481880270062	0.69897000433602	1.07918124604762	2	1	1
'Armadillo'	0.54406804435028	1.03342375548695	14.3	0.49136169383427	0.81291335664286	2.07918124604762	2	1	1
'O.monkey'	-0.31875876262441	1.19033169817029	15.2	0.25527250510331	1.07918124604762	2.14612803567824	2	2	2
'Patas'	1	2.06069784035361	10	-0.045757490560675	1.30535136944662	2.23044892137827	4	4	4
'Phalanger'	0.20951501454263	1.05690485133647	11.9	0.25527250510331	1.11394335230684	1.23044892137827	2	1	2
'Pig'	2.28330122870355	2.25527250510331	6.5	0.27875360095283	1.43136376415899	2.06069784035361	4	4	4
'Rabbit'	0.39794000867204	1.08278537031645	7.5	-0.045757490560675	1.25527250510331	1.49136169383427	5	5	5
'Rat'	-0.55284196865778	0.27875360095283	10.6	0.41497334797082	0.67209785793572	1.32221929473392	3	1	3
'Fox'	0.62736585659273	1.70243053644553	7.4	0.38021124171161	0.99122607569249	1.7160033436348	1	1	1
'Rhesus'	0.83250891270624	2.25285303097989	8.4	0.079181246047625	1.46239799789896	2.2148438480477	2	3	2
'G.hyrax'	-0.1249387366083	1.0899051114394	5.7	-0.045757490560675	0.84509804001426	2.35218251811136	2	2	2
'R.hyrax'	0.55630250076729	1.32221929473392	4.9	-0.30102999566398	0.77815125038364	2.35218251811136	3	2	3
'Sheep'	1.74429298312268	2.24303804868629	3.2	-0.22184874961636	1.30102999566398	2.17897694729317	5	5	5
'Tenrec'	-0.045757490560675	0.41497334797082	11	0.36172783601759	0.65321251377534	1.77815125038364	2	1	2
'T.hyrax'	0.30102999566398	1.0899051114394	4.9	-0.30102999566398	0.8750612633917	2.30102999566398	3	1	3
'Tree_shrew'	-1	0.39794000867204	13.2	0.41497334797082	0.36172783601759	1.66275783168157	3	2	2
'Vervet'	0.6222140229663	1.76342799356294	9.7	-0.22184874961636	1.38021124171161	2.32221929473392	4	3	4
'L.opossum'	0.54406804435028	0.5910646070265	12.8	0.81954393554187	0.47712125471966	1.14612803567824	2	1	1

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	0 seconds
R Server	Big Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=315696&T=0

[TABLE]
[ROW]

Summary of computational transaction[/C][/ROW] [ROW]

Raw Input[/C]

view raw input (R code) [/C][/ROW] [ROW]

Raw Output[/C]

view raw output of R engine [/C][/ROW] [ROW]

Computing time[/C]

0 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=315696&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=315696&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	0 seconds
R Server	Big Analytics Cloud Computing Center

Parameters (Session):

par1 = 3 ;

Parameters (R input):

par1 = 3 ;

R code (references can be found in the software module):

library(psych)
par1 <- as.numeric(par1)
x <- t(x)
nrows <- length(x[,1])
ncols <- length(x[1,])
y <- array(as.double(x[1:nrows,2:ncols]),dim=c(nrows,ncols-1))
colnames(y) <- colnames(x)[2:ncols]
rownames(y) <- x[,1]
print(y)
fit <- principal(y, nfactors=par1, rotate='varimax')
fit
fs <- factor.scores(y,fit)
fs
bitmap(file='test2.png')
plot(fs$scores,pch=20)
text(fs$scores,labels=rownames(y),pos=3)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Rotated Factor Loadings',par1+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variables',1,TRUE)
for (i in 1:par1) {
a<-table.element(a,paste('Factor',i,sep=''),1,TRUE)
}
a<-table.row.end(a)
for (j in 1:length(fit$loadings[,1])) {
a<-table.row.start(a)
a<-table.element(a,rownames(fit$loadings)[j],header=TRUE)
for (i in 1:par1) {
a<-table.element(a,round(fit$loadings[j,i],3))
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code