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步芽

【极致中配】IIT 计量经济学导论

系统讲授计量经济学：从经典线性回归、假设检验、多元回归到虚拟变量、多重共线性、自相关、异方差及Logit/Probit/Tobit模型，并配合STATA实操。

难度
难度 4/5 — 需线性代数、概率统计与回归基础，涵盖到研究生级的定性响应与异方差处理
适合人群
有统计基础、想系统掌握回归建模与实证分析的经济/金融专业学生及研究者
前置要求
概率论与数理统计（估计量性质、假设检验的基础）、线性代数（多元回归的矩阵表达）、微积分（最小二乘与最大似然推导）、STATA 基础（课程含大量 STATA 实操，可边学边补）
课程规模
65 讲 · 2172播放
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主题覆盖

计量经济学导论估计量的优良性质经典线性回归模型拟合优度与方差分析假设检验STATA实操多元线性回归与F检验Chow检验与结构突变虚拟变量与双重差分多重共线性自相关与异方差Logit/Probit/Tobit模型

课程大纲（65 讲）

  1. P1 · #1 Introduction to Econometrics & Econometric Analysis | Part 112 分钟
  2. P2 · #2 Introduction to Econometrics & Econometric Analysis | Part 218 分钟
  3. P3 · #3 Different Steps in Econometric Analysis | Part 118 分钟
  4. P4 · #4 Different Steps in Econometric Analysis | Part 214 分钟
  5. P5 · #5 Desirable Properties of the Estimates of the Population Parameters | Part 120 分钟
  6. P6 · #6 Desirable Properties of the Estimates of the Population Parameters | Part 213 分钟
  7. P7 · #7 Classical Linear Regression Model | Part 115 分钟
  8. P8 · #8 Classical Linear Regression Model | Part 221 分钟
  9. P9 · #9 Classical Linear Regression Model | Part 320 分钟
  10. P10 · #10 Classical Linear Regression Model | Part 420 分钟
  11. P11 · #11 Classical Linear Regression Model | Part 521 分钟
  12. P12 · #12 Goodness of Fit Measure | Anova & Hypothesis Testing | Part 116 分钟
  13. P13 · #13 Goodness of Fit Measure | Anova & Hypothesis Testing | Part 221 分钟
  14. P14 · #14 Goodness of Fit Measure | Anova & Hypothesis Testing | Part 319 分钟
  15. P15 · #15 Goodness of Fit Measure | Anova & Hypothesis Testing | Part 421 分钟
  16. P16 · #16 Goodness of Fit Measure | Anova & Hypothesis Testing | Part 525 分钟
  17. P17 · #17 Application of STATA for Hypothesis Testing | Part 122 分钟
  18. P18 · #18 Application of STATA for Hypothesis Testing | Part 216 分钟
  19. P19 · #19 Application of STATA for Hypothesis Testing | Part 346 分钟
  20. P20 · #20 Application of STATA for Hypothesis Testing | Part 416 分钟
  21. P21 · #21 Application of STATA for Hypothesis Testing | Part 523 分钟
  22. P22 · #22 Multiple Linear Regression Model | Application of F Statistics | Part 121 分钟
  23. P23 · #23 Multiple Linear Regression Model | Application of F Statistics | Part 217 分钟
  24. P24 · #24 Multiple Linear Regression Model | Application of F Statistics | Part 321 分钟
  25. P25 · #25 Multiple Linear Regression Model | Application of F Statistics | Part 414 分钟
  26. P26 · #26 Multiple Linear Regression Model | Application of F Statistics | Part 517 分钟
  27. P27 · #27 Multiple Linear Regression Model | Application of F Statistics | Part 618 分钟
  28. P28 · #28 Structural Break Analysis Using Chow Test | Part 120 分钟
  29. P29 · #29 Structural Break Analysis Using Chow Test | Part 219 分钟
  30. P30 · #30 Structural Break Analysis Using Chow Test | Part 318 分钟
  31. P31 · #31 Structural Break Analysis Using Chow Test | Part 415 分钟
  32. P32 · #32 Structural Break Analysis Using Chow Test | Part 515 分钟
  33. P33 · #33 Dummy Variable Analysis | Part 1 | Application of Difference in Difference f22 分钟
  34. P34 · #34 Dummy Variable Analysis | Part 2 | Application of Difference in Difference f16 分钟
  35. P35 · #35 Dummy Variable Analysis | Part 3 | Application of Difference in Difference f22 分钟
  36. P36 · #36 Dummy Variable Analysis | Part 4 | Application of Difference in Difference f13 分钟
  37. P37 · #37 Dummy Variable Analysis | Part 5 | Application of Difference in Difference f22 分钟
  38. P38 · #38 Statistical Analysis of Dummy Variable Models & Testing for Seasonal Fluctua18 分钟
  39. P39 · #39 Statistical Analysis of Dummy Variable Models & Testing for Seasonal Fluctua19 分钟
  40. P40 · #40 Statistical Analysis of Dummy Variable Models & Testing for Seasonal Fluctua16 分钟
  41. P41 · 40_Statistical_Analysis_of_Dummy_Variable_Models_Testing_for_Seasonal_Fluctuatio17 分钟
  42. P42 · 41_Qualitative_Response_Models_Linear_Probability_Model_Logit_Probit_Models_Part19 分钟
  43. P43 · #41 Statistical Analysis of Dummy Variable Models & Testing for Seasonal Fluctua16 分钟
  44. P44 · 42_Qualitative_Response_Models_Linear_Probability_Model_Logit_Probit_Models_Part16 分钟
  45. P45 · #42 Statistical Analysis of Dummy Variable Models & Testing for Seasonal Fluctua19 分钟
  46. P46 · 43_Qualitative_Response_Models_Linear_Probability_Model_Logit_Probit_Models_Part18 分钟
  47. P47 · #43 Statistical Analysis of Dummy Variable Models & Testing for Seasonal Fluctua21 分钟
  48. P48 · #44 Relaxing the Assumptions of CLRM Multicollinearity & AutoCorrelation |Part119 分钟
  49. P49 · #45 Relaxing the Assumptions of CLRM Multicollinearity & AutoCorrelation |Part217 分钟
  50. P50 · #46 Relaxing the Assumptions of CLRM Multicollinearity & AutoCorrelation |Part323 分钟
  51. P51 · #47 Relaxing the Assumptions of CLRM Multicollinearity & AutoCorrelation |Part415 分钟
  52. P52 · #48 Relaxing the Assumptions of CLRM Multicollinearity & AutoCorrelation |Part520 分钟
  53. P53 · #49 Relaxing the Assumptions of CLRM Multicollinearity & AutoCorrelation |Part621 分钟
  54. P54 · #50 Relaxing the Assumptions of CLRM Autocorrelation & Heteroscedasticity |Part121 分钟
  55. P55 · #51 Relaxing the Assumptions of CLRM Autocorrelation & Heteroscedasticity |Part223 分钟
  56. P56 · #52 Relaxing the Assumptions of CLRM Autocorrelation & Heteroscedasticity |Part314 分钟
  57. P57 · #53 Relaxing the Assumptions of CLRM Autocorrelation & Heteroscedasticity |Part416 分钟
  58. P58 · #54 Relaxing the Assumptions of CLRM Autocorrelation & Heteroscedasticity |Part516 分钟
  59. P59 · #55 Relaxing the Assumptions of CLRM Autocorrelation & Heteroscedasticity|Part418 分钟
  60. P60 · #60 Qualitative Response Models | Linear Probability Model | Logit | Probit Mode16 分钟
  61. P61 · #61 Qualitative Response Models | Probit | Tobit Models | Part 1 | Introduction21 分钟
  62. P62 · #62 Qualitative Response Models | Probit | Tobit Models | Part 2 | Introduction17 分钟
  63. P63 · #63 Qualitative Response Models | Probit | Tobit Models | Part 3 | Introduction15 分钟
  64. P64 · #64 Qualitative Response Models | Probit | Tobit Models | Part 4 | Introduction17 分钟
  65. P65 · #65 Qualitative Response Models | Probit | Tobit Models | Part 5 | Introduction18 分钟

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