Data: https://pan.baidu.com/s/1VlTy4nfvgXdDzgimVguZMg
Data Display:
| Coupon code | date | Traditional car sales | Quarter gross domestic product value ($ billion) x1 | Gasoline prices (yuan / ton) x2 | RMB benchmark lending rate% x3 | Automobile production (ten thousand) x4 | Highway mileage | Automobile stock index | Consumer Confidence Index |
| 65 | In 2003 Q1 | 102.1 | 29825.5 | 3020 | 5.49 | 102.1 | 177.6375 | 1696.81 | 97.7 |
| 64 | In 2003 Q2 | 110 | 32537.3 | 3020 | 5.49 | 110 | 178.755 | 1912.54 | 87.66666667 |
| 63 | In 2003 Q3 | 112.1 | 35291.9 | 2920 | 5.49 | 112.1 | 179.8725 | 1803.71 | 92.33333333 |
| 62 | In 2003 Q4 | 122.8 | 39767.4 | 3010 | 5.49 | 122.8 | 180.99 | 1922.48 | 94.66666667 |
| 61 | In 2004 Q1 | 131.1 | 34544.6 | 3210 | 5.49 | 131.1 | 182.5125 | 1930.71 | 95.33333333 |
| 60 | In 2004 Q2 | 133.3 | 38700.8 | 3210 | 5.49 | 133.3 | 184.035 | 1245.7 | 92.56666667 |
| 59 | In 2004 Q3 | 121 | 41855 | 3510 | 5.49 | 121 | 185.5575 | 1163.16 | 91.06666667 |
| 58 | 2004 Q4 | 123.7 | 46739.8 | 3750 | 5.76 | 123.7 | 187.08 | 870.61 | 92.56666667 |
| 57 | In 2005 Q1 | 139.7 | 40453.3 | 3750 | 5.76 | 139.7 | 188.5675 | 749.62 | 93.93333333 |
| 56 | In 2005 Q2 | 162.2 | 44793.1 | 4050 | 5.76 | 162.2 | 190.055 | 764.84 | 94.53333333 |
Data Description:
| Field Name | Null Statistics | Means | Standard deviation |
| Coupon code | 0 | ||
| date | 0 | ||
| Traditional car sales | 0 | 425.237538 | 221.897082 |
| Quarter gross domestic product value ($ billion) x1 | 0 | 118112.425 | 61932.8968 |
| Gasoline prices (yuan / ton) x2 | 0 | 6233.43077 | 1922.62741 |
| RMB benchmark lending rate% x3 | 0 | 5.77615385 | 0.77781081 |
| Automobile production (ten thousand) x4 | 0 | 430.432462 | 228.089876 |
| Highway mileage | 1 | 369.646328 | 101.389938 |
| Automobile stock index | 0 | 3628.72494 | 1805.48337 |
| Consumer Confidence Index | 0 | 102.133333 | 8.68642379 |
Above table can be seen in the fields highway mileage has a missing value, GDP quarter value ($ billion) x1 mean and standard deviation are the largest, too understanding of the automotive industry, we can only show you a simple analysis
First fill missing values mean
Excel regression analysis, regression analysis is to demonstrate the following table, meanings can refer to specific indicators: https://zhuanlan.zhihu.com/p/57875710
| SUMMARY OUTPUT | ||||||||
| Regression | ||||||||
| Multiple R | 0.99957873 | |||||||
| R Square | 0.99915764 | |||||||
| Adjusted R Square | 0.9990705 | |||||||
| Standard Error | 6.76514348 | |||||||
| Observations | 65 | |||||||
| variance analysis | ||||||||
| df | SS | MS | F | Significance F | ||||
| regression analysis | 6 | 3148597.65 | 524766.276 | 11465.9988 | 3.2078E-87 | |||
| Residual | 58 | 2654.49565 | 45.7671663 | |||||
| total | 64 | 3151252.15 | ||||||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | The lower limit of 95.0% | The upper limit of 95.0% | |
| Intercept | 85.5427723 | 21.9452814 | 3.89800298 | 0.0002541 | 41.6145189 | 129.471026 | 41.6145189 | 129.471026 |
| X Variable 1 | 0.00135989 | 0.00078443 | 1.73359719 | 0.08830297 | -0.0002103 | 0.0029301 | -0.0002103 | 0.0029301 |
| X Variable 2 | 2.38886779 | 1.57731247 | 1.51451779 | 0.13532554 | -0.7684662 | 5.54620173 | -0.7684662 | 5.54620173 |
| X Variable 3 | 0.99479733 | 0.01034768 | 96.1371917 | 1.1819E-65 | 0.97408419 | 1.01551047 | 0.97408419 | 1.01551047 |
| X Variable 4 | -0.0050534 | 0.0244978 | -0.206278 | 0.83729619 | -0.054091 | 0.04398432 | -0.054091 | 0.04398432 |
| X Variable 5 | 0.00139701 | 0.0009863 | 1.41641407 | 0.16200289 | -0.0005773 | 0.0033713 | -0.0005773 | 0.0033713 |
| X Variable 6 | -1.1159425 | 0.1935889 | -5.7644966 | 3.3213E-07 | -1.5034528 | -0.7284323 | -1.5034528 | -0.7284323 |
