講者：USER
日期：2021-10-13
觀看: 457
  • 00:00 1.
    Multiple Regression-1
  • 03:17 2.
    The Model
  • 03:22 3.
    Linear Regression Model (1)
  • 09:51 4.
    Linear Regression Model (2)
  • 09:52 5.
    Linear Regression Model (1)
  • 13:25 6.
    Linear Regression Model (2)
  • 19:27 7.
    Linear Regression Model (3)
  • 24:22 8.
    Estimation
  • 24:25 9.
    Find the Least Squares Estimator
  • 33:46 10.
    Estimation
  • 33:47 11.
    Linear Regression Model (3)
  • 34:10 12.
    Linear Regression Model (2)
  • 34:27 13.
    Linear Regression Model (3)
  • 34:59 14.
    Estimation
  • 34:59 15.
    Find the Least Squares Estimator
  • 42:20 16.
    Digression to Derivative of Matrix:
  • 48:10 17.
    Find the Least Squares Estimator
  • 1:03:21 18.
    Second Order Condition
  • 1:05:57 19.
    Positive Definite Matrix
  • 1:09:49 20.
    Second Order Condition
  • 1:16:42 21.
    Digression to Derivative of Matrix:
  • 1:16:44 22.
    Find the Least Squares Estimator
  • 1:17:35 23.
    Digression to Derivative of Matrix:
  • 1:17:37 24.
    Second Order Condition
  • 1:30:45 25.
    Positive Definite Matrix
  • 1:30:46 26.
    Simple Regression Example
  • 1:30:46 27.
    Positive Definite Matrix
  • 1:35:38 28.
    Second Order Condition
  • 1:36:03 29.
    Positive Definite Matrix
  • 1:37:38 30.
    Simple Regression Example
  • 1:37:39 31.
    Estimating Simple Regression
  • 1:37:40 32.
    Simple Regression
  • 1:37:40 33.
    Goodness of Fit
  • 1:37:44 34.
    LS Estimators and Properties
  • 1:37:45 35.
    Goodness of Fit
  • 1:38:03 36.
    LS Estimators and Properties
  • 1:40:12 37.
    Four Assumptions
  • 1:40:20 38.
    Four Assumptions
  • 1:40:24 39.
    Four Assumptions
  • 1:48:47 40.
    Four Assumptions
  • 1:51:58 41.
    Four Assumptions
  • 1:51:58 42.
    LS Estimators and Properties
  • 1:51:59 43.
    Goodness of Fit
  • 1:52:00 44.
    Simple Regression
  • 1:52:00 45.
    Estimating Simple Regression
  • 1:52:01 46.
    Simple Regression Example
  • 1:52:01 47.
    Positive Definite Matrix
  • 1:55:55 48.
    Simple Regression Example
  • 1:55:55 49.
    Estimating Simple Regression
  • 1:55:56 50.
    Simple Regression
  • 1:55:57 51.
    Goodness of Fit
  • 1:55:58 52.
    LS Estimators and Properties
  • 1:55:59 53.
    Four Assumptions
  • 1:56:01 54.
    Four Assumptions
  • 1:56:02 55.
    A Digression to Variance Covariance Matrix of a Vector
  • 1:56:04 56.
    Assumption A3
  • 1:56:04 57.
    A Digression to Variance Covariance Matrix of a Vector
  • 1:56:05 58.
    Four Assumptions
  • 1:56:05 59.
    Four Assumptions
  • 1:56:06 60.
    LS Estimators and Properties
  • 1:56:43 61.
    Four Assumptions
  • 1:56:44 62.
    Four Assumptions
  • 2:04:05 63.
    A Digression to Variance Covariance Matrix of a Vector
  • 2:11:55 64.
    Assumption A3
  • 2:17:05 65.
    A Digression to Variance Covariance Matrix of a Vector
  • 2:17:06 66.
    Four Assumptions
  • 2:18:22 67.
    A Digression to Variance Covariance Matrix of a Vector
  • 2:18:23 68.
    Assumption A3
  • 2:18:24 69.
    Properties of LS Estimator: Unbiased
  • 2:19:07 70.
    Assumption A3
  • 2:19:08 71.
    A Digression to Variance Covariance Matrix of a Vector
  • 2:19:08 72.
    Four Assumptions
  • 2:19:10 73.
    Four Assumptions
  • 2:19:21 74.
    Four Assumptions
  • 2:19:22 75.
    A Digression to Variance Covariance Matrix of a Vector
  • 2:19:23 76.
    Assumption A3
  • 2:19:24 77.
    Properties of LS Estimator: Unbiased
  • 2:28:55 78.
    Assumption A3
  • 2:28:56 79.
    A Digression to Variance Covariance Matrix of a Vector
  • 2:28:56 80.
    Four Assumptions
  • 2:28:58 81.
    Four Assumptions
  • 2:29:04 82.
    Four Assumptions
  • 2:29:16 83.
    Four Assumptions
  • 2:30:17 84.
    A Digression to Variance Covariance Matrix of a Vector
  • 2:30:18 85.
    Assumption A3
  • 2:30:18 86.
    Properties of LS Estimator: Unbiased
  • 2:30:20 87.
    Assumption A3
  • 2:30:20 88.
    Properties of LS Estimator: Unbiased
  • 2:30:24 89.
    VAR-COV Of 𝛽 :VAR( 𝛽 )
  • 2:34:03 90.
    Properties of LS Estimator: Unbiased
  • 2:34:26 91.
    VAR-COV Of 𝛽 :VAR( 𝛽 )
  • 2:42:27 92.
    Properties of LS Estimator: Unbiased
  • 2:42:41 93.
    VAR-COV Of 𝛽 :VAR( 𝛽 )
  • 2:45:01 94.
    What Have We Got So Far?
  • 2:47:39 95.
    Gauss Markov Theorem (I)
  • 2:47:41 96.
    What Have We Got So Far?
  • 2:51:02 97.
    Gauss Markov Theorem (I)
  • 2:55:42 98.
    Gauss Markov Theorem (II)
  • 2:55:45 99.
    Gauss Markov Theorem (III)
  • 2:55:51 100.
    What do we need to do for statistical inference?
  • 2:59:49 101.
    Gauss Markov Theorem (III)
  • 2:59:49 102.
    Gauss Markov Theorem (II)
  • 2:59:50 103.
    Gauss Markov Theorem (I)
  • 2:59:50 104.
    What Have We Got So Far?
  • 2:59:51 105.
    VAR-COV Of 𝛽 :VAR( 𝛽 )
  • 2:59:52 106.
    Properties of LS Estimator: Unbiased
  • 2:59:52 107.
    Assumption A3
  • 2:59:52 108.
    A Digression to Variance Covariance Matrix of a Vector
  • 2:59:53 109.
    Four Assumptions
  • 2:59:53 110.
    Four Assumptions
  • 2:59:53 111.
    LS Estimators and Properties
  • 2:59:54 112.
    Four Assumptions
  • 3:00:51 113.
    Four Assumptions
  • 3:00:52 114.
    Four Assumptions
  • 3:00:58 115.
    Four Assumptions
  • 3:00:59 116.
    A Digression to Variance Covariance Matrix of a Vector
  • 3:00:59 117.
    Assumption A3
  • 3:01:00 118.
    Properties of LS Estimator: Unbiased
  • 3:01:03 119.
    VAR-COV Of 𝛽 :VAR( 𝛽 )
  • 3:01:05 120.
    Properties of LS Estimator: Unbiased
  • 3:01:05 121.
    Assumption A3
  • 3:01:06 122.
    Properties of LS Estimator: Unbiased
  • 3:02:01 123.
    VAR-COV Of 𝛽 :VAR( 𝛽 )
  • 3:02:02 124.
    What Have We Got So Far?
  • 3:02:03 125.
    Gauss Markov Theorem (I)
  • 3:02:05 126.
    Gauss Markov Theorem (II)
  • 3:02:06 127.
    Gauss Markov Theorem (III)
  • 3:02:07 128.
    What do we need to do for statistical inference?
  • 3:02:14 129.
    Properties of the OLS Estimator
  • 3:07:49 130.
    Statistical Inference
  • 3:08:20 131.
    The Presidential Election Example
  • 3:08:23 132.
    Hypothesis Testing
  • 3:08:24 133.
    Statistical Inference
  • 3:08:26 134.
    Properties of the OLS Estimator
  • 3:08:27 135.
    Statistical Inference
  • 3:08:28 136.
    Hypothesis Testing
  • 3:08:28 137.
    The Presidential Election Example
  • 3:10:48 138.
    The Outcome of the US Presidential Election 1892-2012
  • 3:14:10 139.
    The US Presidential Election Again
  • 3:14:11 140.
    The Outcome of the US Presidential Election 1892-2012
  • 3:14:37 141.
    The US Presidential Election Again
  • 3:14:57 142.
    The Outcome of the US Presidential Election 1892-2012
  • 3:15:06 143.
    The US Presidential Election Again
  • 3:15:07 144.
    The Presidential Election
  • 3:15:11 145.
    The US Presidential Election Again
  • 3:15:11 146.
    The Outcome of the US Presidential Election 1892-2012
  • 3:15:34 147.
    The US Presidential Election Again
  • 3:17:09 148.
    The Presidential Election
  • 3:18:56 149.
    The US Presidential Election Again
  • 3:19:32 150.
    The Presidential Election
  • 3:21:25 151.
    The US Presidential Election Again
  • 3:21:25 152.
    The Outcome of the US Presidential Election 1892-2012
  • 3:21:26 153.
    The Presidential Election Example
  • 3:21:27 154.
    Hypothesis Testing
  • 3:21:28 155.
    Statistical Inference
  • 3:21:29 156.
    Properties of the OLS Estimator
  • 3:21:52 157.
    Statistical Inference
  • 3:21:52 158.
    Hypothesis Testing
  • 3:21:53 159.
    The Presidential Election Example
  • 3:21:53 160.
    The Outcome of the US Presidential Election 1892-2012
  • 3:21:54 161.
    The US Presidential Election Again
  • 3:21:55 162.
    The Presidential Election
  • 3:25:37 163.
    Presidential Election Estimation
  • 3:26:52 164.
    The Presidential Election
  • 3:27:06 165.
    Presidential Election Estimation
  • 3:27:19 166.
    Hypothesis Testing: Ex. 3a)
  • 3:27:21 167.
    Presidential Election Estimation
  • 3:27:21 168.
    The Presidential Election
  • 3:27:34 169.
    Presidential Election Estimation
  • 3:28:22 170.
    Hypothesis Testing: Ex. 3a)
  • 3:29:29 171.
    Presidential Election Estimation
  • 3:29:30 172.
    The Presidential Election
  • 3:29:43 173.
    Presidential Election Estimation
  • 3:30:04 174.
    Hypothesis Testing: Ex. 3a)
  • 3:31:42 175.
    Alternative Test for H0: b2 =b3 (b2-b3 =0)
  • 3:31:43 176.
    Hypothesis Testing: Ex. 3a)
  • 3:31:44 177.
    Presidential Election Estimation
  • 3:34:03 178.
    Hypothesis Testing: Ex. 3a)
  • 3:34:05 179.
    Presidential Election Estimation
  • 3:34:05 180.
    The Presidential Election
  • 3:34:07 181.
    The US Presidential Election Again
  • 3:34:09 182.
    The Presidential Election
  • 3:34:10 183.
    Presidential Election Estimation
  • 3:34:15 184.
    Hypothesis Testing: Ex. 3a)
  • 3:34:36 185.
    Alternative Test for H0: b2 =b3 (b2-b3 =0)
  • 3:34:38 186.
    Hypothesis Testing: Ex. 3a)
  • 3:34:39 187.
    Presidential Election Estimation
  • 3:34:50 188.
    Hypothesis Testing: Ex. 3a)
  • 3:35:09 189.
    Alternative Test for H0: b2 =b3 (b2-b3 =0)
  • 3:37:19 190.
    Hypothesis Testing: Ex. 3a)
  • 3:37:19 191.
    Presidential Election Estimation
  • 3:37:20 192.
    The Presidential Election
  • 3:37:46 193.
    Presidential Election Estimation
  • 3:37:46 194.
    Hypothesis Testing: Ex. 3a)
  • 3:37:47 195.
    Alternative Test for H0: b2 =b3 (b2-b3 =0)
  • 3:37:50 196.
    Hypothesis Testing: Ex. 3a)
  • 3:37:51 197.
    Presidential Election Estimation
  • 3:37:51 198.
    The Presidential Election
  • 3:38:28 199.
    Presidential Election Estimation
  • 3:38:29 200.
    Hypothesis Testing: Ex. 3a)
  • 3:38:30 201.
    Alternative Test for H0: b2 =b3 (b2-b3 =0)
  • 3:38:47 202.
    Hypothesis Testing: Ex. 3a)
  • 3:38:50 203.
    Alternative Test for H0: b2 =b3 (b2-b3 =0)
  • 3:39:05 204.
    Statistical Inference for Linear Restrictions
  • 3:39:06 205.
    Alternative Test for H0: b2 =b3 (b2-b3 =0)
  • 3:39:12 206.
    Hypothesis Testing: Ex. 3a)
  • 3:39:13 207.
    Presidential Election Estimation
  • 索引
  • 筆記
  • 討論
  • 全螢幕
acct-multiple regression-20211013
長度: 3:39:46, 瀏覽: 458, 最近修訂: 2021-10-13
    上一篇 下一篇
    • 00:00 1.
      Multiple Regression-1
    • 03:17 2.
      The Model
    • 03:22 3.
      Linear Regression Model (1)
    • 09:51 4.
      Linear Regression Model (2)
    • 09:52 5.
      Linear Regression Model (1)
    • 13:25 6.
      Linear Regression Model (2)
    • 19:27 7.
      Linear Regression Model (3)
    • 24:22 8.
      Estimation
    • 24:25 9.
      Find the Least Squares Estimator
    • 33:46 10.
      Estimation
    • 33:47 11.
      Linear Regression Model (3)
    • 34:10 12.
      Linear Regression Model (2)
    • 34:27 13.
      Linear Regression Model (3)
    • 34:59 14.
      Estimation
    • 34:59 15.
      Find the Least Squares Estimator
    • 42:20 16.
      Digression to Derivative of Matrix:
    • 48:10 17.
      Find the Least Squares Estimator
    • 1:03:21 18.
      Second Order Condition
    • 1:05:57 19.
      Positive Definite Matrix
    • 1:09:49 20.
      Second Order Condition
    • 1:16:42 21.
      Digression to Derivative of Matrix:
    • 1:16:44 22.
      Find the Least Squares Estimator
    • 1:17:35 23.
      Digression to Derivative of Matrix:
    • 1:17:37 24.
      Second Order Condition
    • 1:30:45 25.
      Positive Definite Matrix
    • 1:30:46 26.
      Simple Regression Example
    • 1:30:46 27.
      Positive Definite Matrix
    • 1:35:38 28.
      Second Order Condition
    • 1:36:03 29.
      Positive Definite Matrix
    • 1:37:38 30.
      Simple Regression Example
    • 1:37:39 31.
      Estimating Simple Regression
    • 1:37:40 32.
      Simple Regression
    • 1:37:40 33.
      Goodness of Fit
    • 1:37:44 34.
      LS Estimators and Properties
    • 1:37:45 35.
      Goodness of Fit
    • 1:38:03 36.
      LS Estimators and Properties
    • 1:40:12 37.
      Four Assumptions
    • 1:40:20 38.
      Four Assumptions
    • 1:40:24 39.
      Four Assumptions
    • 1:48:47 40.
      Four Assumptions
    • 1:51:58 41.
      Four Assumptions
    • 1:51:58 42.
      LS Estimators and Properties
    • 1:51:59 43.
      Goodness of Fit
    • 1:52:00 44.
      Simple Regression
    • 1:52:00 45.
      Estimating Simple Regression
    • 1:52:01 46.
      Simple Regression Example
    • 1:52:01 47.
      Positive Definite Matrix
    • 1:55:55 48.
      Simple Regression Example
    • 1:55:55 49.
      Estimating Simple Regression
    • 1:55:56 50.
      Simple Regression
    • 1:55:57 51.
      Goodness of Fit
    • 1:55:58 52.
      LS Estimators and Properties
    • 1:55:59 53.
      Four Assumptions
    • 1:56:01 54.
      Four Assumptions
    • 1:56:02 55.
      A Digression to Variance Covariance Matrix of a Vector
    • 1:56:04 56.
      Assumption A3
    • 1:56:04 57.
      A Digression to Variance Covariance Matrix of a Vector
    • 1:56:05 58.
      Four Assumptions
    • 1:56:05 59.
      Four Assumptions
    • 1:56:06 60.
      LS Estimators and Properties
    • 1:56:43 61.
      Four Assumptions
    • 1:56:44 62.
      Four Assumptions
    • 2:04:05 63.
      A Digression to Variance Covariance Matrix of a Vector
    • 2:11:55 64.
      Assumption A3
    • 2:17:05 65.
      A Digression to Variance Covariance Matrix of a Vector
    • 2:17:06 66.
      Four Assumptions
    • 2:18:22 67.
      A Digression to Variance Covariance Matrix of a Vector
    • 2:18:23 68.
      Assumption A3
    • 2:18:24 69.
      Properties of LS Estimator: Unbiased
    • 2:19:07 70.
      Assumption A3
    • 2:19:08 71.
      A Digression to Variance Covariance Matrix of a Vector
    • 2:19:08 72.
      Four Assumptions
    • 2:19:10 73.
      Four Assumptions
    • 2:19:21 74.
      Four Assumptions
    • 2:19:22 75.
      A Digression to Variance Covariance Matrix of a Vector
    • 2:19:23 76.
      Assumption A3
    • 2:19:24 77.
      Properties of LS Estimator: Unbiased
    • 2:28:55 78.
      Assumption A3
    • 2:28:56 79.
      A Digression to Variance Covariance Matrix of a Vector
    • 2:28:56 80.
      Four Assumptions
    • 2:28:58 81.
      Four Assumptions
    • 2:29:04 82.
      Four Assumptions
    • 2:29:16 83.
      Four Assumptions
    • 2:30:17 84.
      A Digression to Variance Covariance Matrix of a Vector
    • 2:30:18 85.
      Assumption A3
    • 2:30:18 86.
      Properties of LS Estimator: Unbiased
    • 2:30:20 87.
      Assumption A3
    • 2:30:20 88.
      Properties of LS Estimator: Unbiased
    • 2:30:24 89.
      VAR-COV Of 𝛽 :VAR( 𝛽 )
    • 2:34:03 90.
      Properties of LS Estimator: Unbiased
    • 2:34:26 91.
      VAR-COV Of 𝛽 :VAR( 𝛽 )
    • 2:42:27 92.
      Properties of LS Estimator: Unbiased
    • 2:42:41 93.
      VAR-COV Of 𝛽 :VAR( 𝛽 )
    • 2:45:01 94.
      What Have We Got So Far?
    • 2:47:39 95.
      Gauss Markov Theorem (I)
    • 2:47:41 96.
      What Have We Got So Far?
    • 2:51:02 97.
      Gauss Markov Theorem (I)
    • 2:55:42 98.
      Gauss Markov Theorem (II)
    • 2:55:45 99.
      Gauss Markov Theorem (III)
    • 2:55:51 100.
      What do we need to do for statistical inference?
    • 2:59:49 101.
      Gauss Markov Theorem (III)
    • 2:59:49 102.
      Gauss Markov Theorem (II)
    • 2:59:50 103.
      Gauss Markov Theorem (I)
    • 2:59:50 104.
      What Have We Got So Far?
    • 2:59:51 105.
      VAR-COV Of 𝛽 :VAR( 𝛽 )
    • 2:59:52 106.
      Properties of LS Estimator: Unbiased
    • 2:59:52 107.
      Assumption A3
    • 2:59:52 108.
      A Digression to Variance Covariance Matrix of a Vector
    • 2:59:53 109.
      Four Assumptions
    • 2:59:53 110.
      Four Assumptions
    • 2:59:53 111.
      LS Estimators and Properties
    • 2:59:54 112.
      Four Assumptions
    • 3:00:51 113.
      Four Assumptions
    • 3:00:52 114.
      Four Assumptions
    • 3:00:58 115.
      Four Assumptions
    • 3:00:59 116.
      A Digression to Variance Covariance Matrix of a Vector
    • 3:00:59 117.
      Assumption A3
    • 3:01:00 118.
      Properties of LS Estimator: Unbiased
    • 3:01:03 119.
      VAR-COV Of 𝛽 :VAR( 𝛽 )
    • 3:01:05 120.
      Properties of LS Estimator: Unbiased
    • 3:01:05 121.
      Assumption A3
    • 3:01:06 122.
      Properties of LS Estimator: Unbiased
    • 3:02:01 123.
      VAR-COV Of 𝛽 :VAR( 𝛽 )
    • 3:02:02 124.
      What Have We Got So Far?
    • 3:02:03 125.
      Gauss Markov Theorem (I)
    • 3:02:05 126.
      Gauss Markov Theorem (II)
    • 3:02:06 127.
      Gauss Markov Theorem (III)
    • 3:02:07 128.
      What do we need to do for statistical inference?
    • 3:02:14 129.
      Properties of the OLS Estimator
    • 3:07:49 130.
      Statistical Inference
    • 3:08:20 131.
      The Presidential Election Example
    • 3:08:23 132.
      Hypothesis Testing
    • 3:08:24 133.
      Statistical Inference
    • 3:08:26 134.
      Properties of the OLS Estimator
    • 3:08:27 135.
      Statistical Inference
    • 3:08:28 136.
      Hypothesis Testing
    • 3:08:28 137.
      The Presidential Election Example
    • 3:10:48 138.
      The Outcome of the US Presidential Election 1892-2012
    • 3:14:10 139.
      The US Presidential Election Again
    • 3:14:11 140.
      The Outcome of the US Presidential Election 1892-2012
    • 3:14:37 141.
      The US Presidential Election Again
    • 3:14:57 142.
      The Outcome of the US Presidential Election 1892-2012
    • 3:15:06 143.
      The US Presidential Election Again
    • 3:15:07 144.
      The Presidential Election
    • 3:15:11 145.
      The US Presidential Election Again
    • 3:15:11 146.
      The Outcome of the US Presidential Election 1892-2012
    • 3:15:34 147.
      The US Presidential Election Again
    • 3:17:09 148.
      The Presidential Election
    • 3:18:56 149.
      The US Presidential Election Again
    • 3:19:32 150.
      The Presidential Election
    • 3:21:25 151.
      The US Presidential Election Again
    • 3:21:25 152.
      The Outcome of the US Presidential Election 1892-2012
    • 3:21:26 153.
      The Presidential Election Example
    • 3:21:27 154.
      Hypothesis Testing
    • 3:21:28 155.
      Statistical Inference
    • 3:21:29 156.
      Properties of the OLS Estimator
    • 3:21:52 157.
      Statistical Inference
    • 3:21:52 158.
      Hypothesis Testing
    • 3:21:53 159.
      The Presidential Election Example
    • 3:21:53 160.
      The Outcome of the US Presidential Election 1892-2012
    • 3:21:54 161.
      The US Presidential Election Again
    • 3:21:55 162.
      The Presidential Election
    • 3:25:37 163.
      Presidential Election Estimation
    • 3:26:52 164.
      The Presidential Election
    • 3:27:06 165.
      Presidential Election Estimation
    • 3:27:19 166.
      Hypothesis Testing: Ex. 3a)
    • 3:27:21 167.
      Presidential Election Estimation
    • 3:27:21 168.
      The Presidential Election
    • 3:27:34 169.
      Presidential Election Estimation
    • 3:28:22 170.
      Hypothesis Testing: Ex. 3a)
    • 3:29:29 171.
      Presidential Election Estimation
    • 3:29:30 172.
      The Presidential Election
    • 3:29:43 173.
      Presidential Election Estimation
    • 3:30:04 174.
      Hypothesis Testing: Ex. 3a)
    • 3:31:42 175.
      Alternative Test for H0: b2 =b3 (b2-b3 =0)
    • 3:31:43 176.
      Hypothesis Testing: Ex. 3a)
    • 3:31:44 177.
      Presidential Election Estimation
    • 3:34:03 178.
      Hypothesis Testing: Ex. 3a)
    • 3:34:05 179.
      Presidential Election Estimation
    • 3:34:05 180.
      The Presidential Election
    • 3:34:07 181.
      The US Presidential Election Again
    • 3:34:09 182.
      The Presidential Election
    • 3:34:10 183.
      Presidential Election Estimation
    • 3:34:15 184.
      Hypothesis Testing: Ex. 3a)
    • 3:34:36 185.
      Alternative Test for H0: b2 =b3 (b2-b3 =0)
    • 3:34:38 186.
      Hypothesis Testing: Ex. 3a)
    • 3:34:39 187.
      Presidential Election Estimation
    • 3:34:50 188.
      Hypothesis Testing: Ex. 3a)
    • 3:35:09 189.
      Alternative Test for H0: b2 =b3 (b2-b3 =0)
    • 3:37:19 190.
      Hypothesis Testing: Ex. 3a)
    • 3:37:19 191.
      Presidential Election Estimation
    • 3:37:20 192.
      The Presidential Election
    • 3:37:46 193.
      Presidential Election Estimation
    • 3:37:46 194.
      Hypothesis Testing: Ex. 3a)
    • 3:37:47 195.
      Alternative Test for H0: b2 =b3 (b2-b3 =0)
    • 3:37:50 196.
      Hypothesis Testing: Ex. 3a)
    • 3:37:51 197.
      Presidential Election Estimation
    • 3:37:51 198.
      The Presidential Election
    • 3:38:28 199.
      Presidential Election Estimation
    • 3:38:29 200.
      Hypothesis Testing: Ex. 3a)
    • 3:38:30 201.
      Alternative Test for H0: b2 =b3 (b2-b3 =0)
    • 3:38:47 202.
      Hypothesis Testing: Ex. 3a)
    • 3:38:50 203.
      Alternative Test for H0: b2 =b3 (b2-b3 =0)
    • 3:39:05 204.
      Statistical Inference for Linear Restrictions
    • 3:39:06 205.
      Alternative Test for H0: b2 =b3 (b2-b3 =0)
    • 3:39:12 206.
      Hypothesis Testing: Ex. 3a)
    • 3:39:13 207.
      Presidential Election Estimation
    位置
    1. 知識庫
    2. ...
    3. 其它
    資料夾名稱
    其它
    發表人
    李阿乙
    單位
    powercam.fju.edu.tw (root)
    建立
    2021-10-13 22:21:51
    最近修訂
    2021-10-13 23:11:00
    長度
    3:39:46
    © Copyright since 2017 by FormosaSoft Corporation.
    All rights reserved.