Data:

0.0130338 -0.0078431 -0.0031889 -0.0447693 0.0052151

0.0084862 0.0166886 -0.0062100 0.0119560 0.0134890

-0.0179153 -0.0086393 0.0100360 0.0000000 -0.0061428

0.0215589 -0.0034858 0.0174353 -0.0285917 -0.0069534

0.0108225 0.0037167 -0.0101345 0.0291900 0.0409751

0.0101713 -0.0121978 -0.0083768 0.0137083 0.0029895

0.0111288 0.0280044 0.0080721 0.0305433 0.0032290

0.0484801 -0.0051480 0.0182495 0.0063348 0.0076752

-0.0344914 -0.0137991 -0.0080468 -0.0299011 -0.0108108

-0.0046596 0.0209882 -0.0060841 -0.0203940 -0.0126677

-0.0018205 -0.0055675 -0.0107587 -0.0089898 -0.0183648

0.0148515 0.0346684 -0.0060004 0.0362855 0.0287032

-0.0092426 -0.0052029 0.0047161 0.0264916 0.0129547

-0.0458668 -0.0278243 -0.0142696 0.0374776 0.0332022

-0.0244432 -0.0182914 0.0059048 -0.0259572 -0.0202333

-0.0183742 -0.0140289 0.0011361 0.0073284 -0.0097182

-0.0297788 -0.0284571 -0.0164555 0.0310847 0.0164377

-0.0225080 -0.0228833 0.0344231 -0.0062006 0.0067584

0.0119617 -0.0067916 0.0185908 -0.0193632 -0.0153440

0.0209811 0.0240509 0.0129586 0.0355419 0.0150962

0.0118669 0.0025328 -0.0036036 0.0021186 0.0028784

0.0140160 0.0172255 0.0003617 0.0150106 0.0141115

-0.0149506 0.0031610 -0.0001808 0.0310352 0.0226415

0.0203322 -0.0148548 -0.0182607 -0.0028283 -0.0161439

0.0112265 -0.0221613 -0.0051565 -0.0247164 0.0105485

-0.0327505 -0.0158879 -0.0037023 0.0143332 0.0164695

-0.0261119 -0.0313390 0.0156076 0.0024575 0.0082154

0.0182675 0.0156863 -0.0219539 -0.0498468 -0.0110910

0.0219907 0.0043436 0.0136551 0.0152655 0.0217441

-0.0331257 -0.0204229 -0.0101495 -0.0186362 -0.0255376

0.0213763 0.0188864 0.0210664 0.0228744 0.0013793

0.0484518 0.0440539 0.0087639 0.0160338 0.0073462

0.0276183 0.0168319 0.0104977 0.0004153 0.0043300

0.0031932 0.0024943 0.0103887 0.0228311 0.0356251

-0.0010610 0.0085953 -0.0023046 -0.0040584 0.0065732

-0.0037175 -0.0060552 0.0035537 0.0114099 0.0211145

0.0023987 -0.0597924 -0.0118626 -0.0251813 -0.0110851

0.0148897 0.0163187 0.0265185 0.0200455 0.0219875

-0.0089075 -0.0068477 0.0047129 0.0129660 0.0196161

-0.0227333 -0.0140276 -0.0069493 0.0024000 -0.0165494

-0.0329997 -0.0313480 -0.0362141 0.0055866 -0.0065208

0.0302098 0.0522778 0.0317662 0.0267857 0.0105865

0.0195493 0.0395079 0.0381773 0.0216425 0.0238843

-0.0045273 0.0204825 0.0174547 0.0253452 0.0059341

-0.0446763 -0.0408118 -0.0163225 -0.0035049 -0.0008137

0.0070008 0.0060451 0.0154081 0.0320252 0.0252443

0.0100111 0.0048532 -0.0016675 -0.0050224 -0.0266084

-0.0112885 0.0057498 0.0100217 -0.0173067 -0.0024480

0.0236703 0.0155500 -0.0162064 0.0001835 -0.0069530

0.0165941 0.0457104 0.0065557 0.0284299 0.0434514

-0.0040139 -0.0118432 -0.0041750 0.0039237 -0.0136175

-0.0069855 0.0098061 0.0003354 -0.0261148 -0.0286114

-0.0154221 -0.0233060 -0.0238055 0.0113097 0.0257467

-0.0252817 0.0088378 -0.0094453 0.0075758 -0.0124498

0.0039470 0.0094174 0.0067614 0.0241676 0.0164701

0.0188149 0.0379692 0.0154985 0.0510400 0.0784157

-0.0055127 -0.0075251 -0.0111921 -0.0044903 0.0198479

-0.0260532 -0.0168492 -0.0080604 0.0432676 0.0587486

0.0128059 -0.0059983 0.0013831 0.0148919 0.0649373

0.0146108 0.0025862 0.0100138 0.0362891 0.0048395

-0.0373858 -0.0126827 -0.0114530 -0.0272533 -0.0396532

-0.0028769 -0.0195950 -0.0070897 -0.0100172 0.0262454

-0.0300058 -0.0497446 -0.0167189 -0.0507510 -0.0583157

-0.0193337 0.0021033 0.0178888 0.0154897 0.0262930

0.0172884 0.0174907 0.0022620 0.0195178 -0.0089331

-0.0163983 0.0077928 -0.0072917 -0.0358752 -0.0636054

0.0275841 0.0125085 -0.0078699 0.0196896 0.0573919

0.0176991 0.0233603 0.0216816 -0.0127639 -0.0401924

0.0034783 -0.0079017 0.0050035 0.0071275 0.0100215

-0.0323512 -0.0146018 -0.0084120 -0.0482225 -0.0628987

0.0465672 0.0410867 0.0349723 0.0152170 0.0056721

-0.0071306 -0.0107828 -0.0086986 0.0303185 0.0517014

-0.0071818 0.0058862 0.0091124 -0.0064473 0.0060779

-0.0031829 0.0017339 -0.0006689 0.0064892 0.0214996

0.0182874 -0.0038944 0.0046854 0.0619937 0.0431379

-0.0142531 -0.0106429 -0.0141572 0.0001557 -0.0450225

-0.0046270 -0.0169045 0.0089542 0.0390661 0.0027938

-0.0072632 0.0075927 0.0000000 -0.0049431 0.0186314

0.0301434 -0.0019947 0.0261219 -0.0307090 -0.0208547

-0.0071023 -0.0430824 -0.0177872 -0.0518714 0.0230447

-0.0128755 -0.0109074 -0.0066456 0.0167076 -0.0126280

0.0028986 0.0030502 -0.0073591 0.0443048 -0.0112340

-0.0265896 -0.0002339 -0.0033698 0.0615551 0.0561091

0.0068290 0.0124006 0.0076078 -0.0419997 -0.0365773

-0.0259510 -0.0240351 -0.0303691 -0.0209345 -0.0068717

0.0136240 0.0182335 0.0086520 0.0568640 0.0387476

0.0209080 0.0165116 0.0089209 -0.0230172 0.0416320

0.0049737 0.0187600 0.0023805 0.0123049 0.0078337

-0.0262009 -0.0044914 -0.0166243 -0.0096353 0.0020622

-0.0041854 0.0060907 -0.0067276 0.0134710 -0.0045908

0.0090063 -0.0022422 0.0000000 -0.0429774 -0.0620229

0.0053555 -0.0083146 0.0069469 -0.0188272 -0.0161072

0.0307783 -0.0160888 0.0031045 -0.0539478 -0.0556609

0.0373241 0.0359281 0.0252751 0.0581879 0.0169708

0.0238029 0.0031125 -0.0068757 0.0122545 0.0281715

0.0256826 0.0525266 0.0406957 -0.0316623 -0.0188482

-0.0060622 0.0086334 0.0058413 0.0445584 0.0305941

0.0217449 0.0229645 0.0291983 0.0084395 0.0319296

0.0033740 -0.0153061 -0.0238245 -0.0016738 -0.0172270

0.0033626 0.0029016 -0.0030507 -0.0012193 -0.0097005

0.0170147 0.0095061 0.0181994 -0.0161758 -0.0075614

0.0103929 -0.0026612 0.0044290 -0.0024818 -0.0164502

-0.0127948 -0.0143678 -0.0187402 -0.0049759 -0.0163732

Please use R studio and give me more details.

8.10. The weekly rates of return for five stocks listed on the New York Stock Exchange are given in Table 8.4. (See the stock-price data on the following website: www.prenhall.com/statistics) (a) Construct the sample covariance matrix S, and find the sample principal components (b) Determine the proportion of the total sample variance explained by the first three (c) Construct Bonferroni simultaneous 90% confidence intervals for the variances (d) Given the results in Parts a-c, do you feel that the stock rates-of-return data can be in (8-20). (Note that the sample mean vector i is displayed in Example 8.5.) principal components. Interpret these components. ? 1, ?2, and ?3 of the first three population components Y, , and K. summarized in fewer than five dimensions? Explain. Table 8.4 Stock-Price Data (Weekly Rate Of Return) Wells Fargo 0.00319 Royal Dutch Shell Exxon Mobil Week Morgan Citibank 0.01303 0.00849 0.01792 0.02156 0.01082 0.01017 0.01113 0.04848 0.03449 0.00466 0.04477 0.01196 0.00784 0.01669 0.00864 0.00349 0.00372 0.01220 0.02800 0.00515 0.01380 0.02099 0.00522 0.01349 0.00614 -0.00695 0.04098 0.00299 0.00323 0.00768 0.01081 0.01267 -0.00621 0.01004 0.01744 0.01013 0.00838 0.00807 0.01825 0.00805 0.00608 0 0.02859 0.02919 0.01371 0.03054 0.00633 0.02990 0.02039 4 10 94 95 96 97 98 0.03732 0.02380 0.02568 0863 0.00606 0.02174 0.03593 0.00311 0.05253 0.02528 0.00688 0.04070 0.00584 0.02920 0.05819 0.01225 0.03166 0.04456 0.00844 0.01697 0.02817 -0.01885 0.03059 0.03193 0.02296 8.10. The weekly rates of return for five stocks listed on the New York Stock Exchange are given in Table 8.4. (See the stock-price data on the following website: www.prenhall.com/statistics) (a) Construct the sample covariance matrix S, and find the sample principal components (b) Determine the proportion of the total sample variance explained by the first three (c) Construct Bonferroni simultaneous 90% confidence intervals for the variances (d) Given the results in Parts a-c, do you feel that the stock rates-of-return data can be in (8-20). (Note that the sample mean vector i is displayed in Example 8.5.) principal components. Interpret these components. ? 1, ?2, and ?3 of the first three population components Y, , and K. summarized in fewer than five dimensions? Explain. Table 8.4 Stock-Price Data (Weekly Rate Of Return) Wells Fargo 0.00319 Royal Dutch Shell Exxon Mobil Week Morgan Citibank 0.01303 0.00849 0.01792 0.02156 0.01082 0.01017 0.01113 0.04848 0.03449 0.00466 0.04477 0.01196 0.00784 0.01669 0.00864 0.00349 0.00372 0.01220 0.02800 0.00515 0.01380 0.02099 0.00522 0.01349 0.00614 -0.00695 0.04098 0.00299 0.00323 0.00768 0.01081 0.01267 -0.00621 0.01004 0.01744 0.01013 0.00838 0.00807 0.01825 0.00805 0.00608 0 0.02859 0.02919 0.01371 0.03054 0.00633 0.02990 0.02039 4 10 94 95 96 97 98 0.03732 0.02380 0.02568 0863 0.00606 0.02174 0.03593 0.00311 0.05253 0.02528 0.00688 0.04070 0.00584 0.02920 0.05819 0.01225 0.03166 0.04456 0.00844 0.01697 0.02817 -0.01885 0.03059 0.03193 0.02296