疫情前後半導體銷售量、來台商務旅客人數與指數
108080017 計財23 林思妤
108080024 計財23 曾柏翰
前言&摘要
研究主題
研究動機
研究方法
數據表
time | value | volume | index | index_tw | travel_num |
---|---|---|---|---|---|
2017-02-01 | 424.9572 | 228.7942 | 133.6150 | 96.73978 | 587.85 |
2017-03-01 | 491.5598 | 267.1257 | 135.6617 | 97.96296 | 867.95 |
2017-04-01 | 460.1660 | 251.5673 | 136.2206 | 98.01368 | 686.85 |
2017-05-01 | 470.3087 | 257.2617 | 143.2015 | 99.93663 | 705.80 |
2017-06-01 | 507.4450 | 285.2962 | 149.3761 | 102.59001 | 712.63 |
2017-07-01 | 495.4272 | 269.9744 | 151.0700 | 104.25918 | 635.33 |
2017-08-01 | 518.6333 | 288.7875 | 152.9965 | 104.36350 | 592.96 |
2017-09-01 | 513.9927 | 277.7596 | 156.4923 | 105.00597 | 698.56 |
2017-10-01 | 511.2647 | 273.2574 | 168.3005 | 106.83854 | 746.43 |
2017-11-01 | 496.4894 | 269.7629 | 171.2014 | 107.43298 | 779.95 |
2017-12-01 | 523.5659 | 296.8445 | 162.2438 | 105.01397 | 563.52 |
2018-01-01 | 480.2926 | 273.2488 | 173.9591 | 110.05376 | 688.42 |
2018-02-01 | 421.0242 | 238.0288 | 171.3492 | 107.17936 | 445.91 |
2018-03-01 | 519.0258 | 300.2092 | 177.0170 | 109.03886 | 648.82 |
2018-04-01 | 495.0086 | 278.1633 | 170.9439 | 107.95844 | 688.91 |
2018-05-01 | 530.2333 | 303.8520 | 164.9545 | 108.17677 | 713.34 |
2018-06-01 | 529.9907 | 295.1851 | 164.7055 | 109.86510 | 756.86 |
2018-07-01 | 558.7390 | 309.9991 | 163.6164 | 108.40215 | 665.63 |
2018-08-01 | 574.0845 | 320.1797 | 170.6935 | 109.09417 | 603.26 |
2018-09-01 | 550.1481 | 306.1936 | 174.8263 | 108.83765 | 689.98 |
2018-10-01 | 575.8847 | 322.5138 | 157.5327 | 100.88356 | 805.94 |
2018-11-01 | 542.7498 | 300.8781 | 151.8636 | 98.21370 | 820.64 |
2018-12-01 | 535.5862 | 292.5254 | 150.5490 | 97.47112 | 587.85 |
2019-01-01 | 521.1001 | 291.5928 | 148.1524 | 97.64715 | 654.67 |
2019-02-01 | 429.6117 | 232.7090 | 158.2385 | 102.10035 | 442.99 |
2019-03-01 | 520.0281 | 283.7669 | 162.4535 | 104.45221 | 841.86 |
2019-04-01 | 517.3198 | 279.0485 | 174.7510 | 108.92154 | 635.54 |
2019-05-01 | 547.4416 | 294.7844 | 166.4468 | 105.74494 | 762.33 |
2019-06-01 | 537.0000 | 302.8798 | 163.6053 | 106.20023 | 672.86 |
2019-07-01 | 576.6764 | 309.4052 | 173.9539 | 108.45697 | 672.18 |
2019-08-01 | 580.4192 | 312.7312 | 173.2629 | 104.69138 | 588.00 |
2019-09-01 | 570.8606 | 308.7360 | 182.9568 | 108.15759 | 718.11 |
2019-10-01 | 594.7036 | 322.4953 | 197.2500 | 111.39816 | 784.83 |
2019-11-01 | 580.1785 | 320.7163 | 208.5952 | 115.58859 | 809.53 |
2019-12-01 | 592.1976 | 327.5462 | 221.2364 | 118.54080 | 641.33 |
2020-01-01 | 547.5676 | 299.4438 | 224.9580 | 119.62323 | 450.76 |
2020-02-01 | 535.7660 | 298.2361 | 219.1889 | 116.23705 | 236.73 |
2020-03-01 | 575.7106 | 324.5329 | 190.8441 | 101.38089 | 56.37 |
2020-04-01 | 562.9757 | 310.2688 | 195.0910 | 103.29479 | 2.34 |
2020-05-01 | 529.9351 | 300.8508 | 202.4785 | 108.76943 | 4.20 |
2020-06-01 | 545.7268 | 313.5967 | 216.4270 | 114.89677 | 7.74 |
2020-07-01 | 574.4404 | 321.3057 | 254.3022 | 122.56210 | 12.23 |
2020-08-01 | 578.6436 | 317.0248 | 284.8738 | 127.43067 | 16.14 |
2020-09-01 | 579.2851 | 318.0076 | 284.6177 | 126.53020 | 15.49 |
2020-10-01 | 583.8427 | 322.3582 | 297.0021 | 128.17761 | 17.92 |
2020-11-01 | 590.1952 | 328.1886 | 312.5038 | 133.93840 | 18.86 |
2020-12-01 | 617.1628 | 351.1447 | 342.2148 | 142.76876 | 12.77 |
2021-01-01 | 625.4524 | 353.8784 | 399.0315 | 155.52204 | 15.22 |
2021-02-01 | 558.5512 | 315.7879 | 425.2685 | 160.80795 | 15.07 |
2021-03-01 | 646.2387 | 367.8464 | 403.5505 | 161.50145 | 18.90 |
2021-04-01 | 645.8933 | 357.9758 | 417.5974 | 171.14845 | 19.20 |
2021-05-01 | 648.6734 | 369.9905 | 394.5038 | 165.04416 | 10.62 |
2021-06-01 | 664.1633 | 369.6717 | 409.1352 | 172.82818 | 0.36 |
2021-07-01 | 708.2470 | 393.5061 | 410.8514 | 176.56940 | 2.91 |
2021-08-01 | 731.4054 | 413.2672 | 409.6727 | 171.31010 | 5.14 |
2021-09-01 | 728.6520 | 415.2158 | 419.9740 | 172.81230 | 6.91 |
2021-10-01 | 732.2672 | 404.6390 | 402.6480 | 167.23556 | 7.83 |
2021-11-01 | 720.4669 | 398.1034 | 423.5164 | 174.89183 | 11.05 |
2021-12-01 | 741.2823 | 417.1858 | 430.4895 | 178.45351 | 7.18 |
2022-01-01 | 710.7607 | 394.5883 | 449.5956 | 182.32857 | 6.43 |
2022-02-01 | 670.6898 | 365.5178 | 436.4967 | 180.56181 | 9.05 |
單一數據走勢圖
- 近五年銷售額走勢圖
- 銷售量走勢圖
- 商務旅客人數柱狀圖
- 半導體類指數走勢圖
- 台灣加權指數走勢圖
各數據比較圖
- 近五年半導體銷售量、銷售額、半導體類指數比較
- 近五年半導體銷售量、商務旅客人數、半導體類指數比較
- 近五年半導體類指數、台灣加權指數比較
數據間相關度與線性回歸
- 銷售量與半導體指數之相關度
## [1] 0.8691962
##
## Pearson's product-moment correlation
##
## data: df$volume and df$index
## t = 13.502, df = 59, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.7903737 0.9197094
## sample estimates:
## cor
## 0.8691962
y = 半導體類指數 x = 半導體產業銷售量
- 來台商務旅客人數與半導體指數之相關度
## [1] -0.8269962
##
## Pearson's product-moment correlation
##
## data: df$index and df$travel_num
## t = -11.299, df = 59, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.8928720 -0.7264653
## sample estimates:
## cor
## -0.8269962
y = 半導體類指數 x = 來台商務旅客人數
結論
延伸思考
Q&A
Where you get your project ideas?
What R techniques have been used?
How many new packages and functions are used?
What is the most difficult part of your analysis?