Chương V :HỒI QUI VỚI BIẾN GIẢ pptx

1 Chương V HỒI QUI VI BIẾN GIẢ Khoa QTKD / ĐHCN tp HCM [...]... Hồi qui v ́i 1 biến định lượng 2 biến định tính k  n: số biến giả; k: số biến định tính; n  (ni  1) ni: số phạm trù của biến i 1 định tính thứ i Thí dụ C.5.3: Thu nhập bác sỹ theo thâm niên (biến định lượng), nơi công tác (biến định tính) gồm thành phố, đồng bằng và miền núi  3 phạm trù và thêm chuyên môn (biến định tính) gồm BS Tây y, Đông y và... ước lượng Yi = α1 + α2 Xi + Ui  Tính RSS v ́i bậc tự do (n1 + n2 – k) v ́i k - số tham số 2/ Ước lượng riêng từng mô hình, tính RSS1 và RSS2 v ́i bậc tự do lần lượt (n1 – k) và (n2 – k) Đặt: RSS  RSS1  RSS2 Voi : RSS  RSS1  RSS2 • 3/ Tính giá trị kiểm định ( RSS  RSS ) / k F0  RSS / ( rằng  2k ) F0> F tới hạn  bác bỏ giả thiết cho n1  n2 2 HQ như nhau F tới hạn:... Hàm 2 biến: Y = 22,67 - 1,5345 X 2 2 biên R  0,9455 Hàm 3 biến: Y = 22,66 – 1,5328 X + 0,0975 Z 2 3biên R  0,9427 18 β1 = 22,66: Nếu không phân biệt khu v ̣c bán hàng và v ́i giá bán cực thấp (X  0), số lượng hàng bán trung bình tối đa là 22,66 tấn / tháng β2= - 1,5328 < 0  giá bán và số lượng hàng bán bán nghịch biến Cùng khu v ̣c bán hàng, khi giá bán tăng (giảm)... lượng hàng bán giảm (tăng) 1,5328 tấn / tháng β3 = 0,0975 quá bé  khu v ̣c bán hàng không có ảnh hưởng nhiều lên số lượng hàng bán 19 β1 = 22,66: Nếu không phân biệt khu v ̣c bán hàng và v ́i giá bán cực thấp (X  0), số lượng hàng bán trung bình tối đa là 22,66 tấn / tháng 20 β2= - 1,5328 < 0  giá bán và số lượng hàng bán bán nghịch biến Cùng khu v ̣c bán hàng,... khi giá bán tăng (giảm) 1 nghìn đ/kg  Số lượng hàng bán giảm (tăng) 1,5328 tấn / tháng 21 β3 = 0,0975 quá bé  khu v ̣c bán hàng không có ảnh hưởng nhiều lên số lượng hàng bán 22 2/ Kiểm định β3 (H0 : β3 = 0)  Chấp nhận H0  β3 không có ý nghĩa thống kê, biến Z không ảnh hưởng lên biến Y  Mô hình hàm 2 biến phù hợp hơn * R2 hàm 2 biến > R2 hàm 3 biến * β3 không có... b2 X + b4 + b6 = (b1 + b4 + b6) + b2 X (Đồng bằng & Đông Y)  Chênh lệch v ̀ thu nhập: (b1 + b3 + b5) - (b1 + b4 + b6) = (b3 + b5) – (b4 + b6) (Cần xét kết hợp v ́i dấu của các tham số hồi quy) 12 IV Kiểm định tính ổn định cấu trúc của các mô hình hồi qui – Kiểm định CHOW • Xét hai hay nhiều hồi qui có khác nhau không Nếu khác, khác tung độ gốc hay hệ số góc hay... hơn * R2 hàm 2 biến > R2 hàm 3 biến * β3 không có ý nghĩa thống kê, biến Z không ảnh hưởng lên Y 3/ Dự báo giá trị trung bình, độ tin cậy 95% (Dựa vào hàm 2 biến) 23 Bài tập 2 1 Giới tính có ảnh hưởng mức lương? 2 Ước lượng hàm hồi quy theo 3 biến trên 3 Dự báo lương khởi điểm một giáo viên nữ có 9 năm kinh nghiệm, độ tin cậy 95% Lương k Điểm (Y) Thâm niên... Dùng mô hình: Yi = β1+ β2Xi + β3D1i + β4D2i + β5D3i + β6D4i + Ui D3i =1  BS Tây y V ́i: Yi : thu nhập (tr đ/năm) Xi : thâm niên (năm) D3i = 0  chuyên môn khác D1i = 1  công tác ở thành phố D4i = 1  BS Đông y D1i = 0  nơi khác D4i = 0  chuyên môn khác D2i = 1  vùng đồng bằng D2i = 0  nơi khác Ví dụ: E1(Y/D1i = 1; D2i=0; D3i=1; D4i=0): Y1=β1+ β2Xi + β3 + β5 + Ui Bác sỹ thâm... RSS / ( rằng  2k ) F0> F tới hạn  bác bỏ giả thiết cho n1  n2 2 HQ như nhau F tới hạn: Fα; (2; n1 +n2 -2k)  Các quan sát ở 2 nhóm không thể gộp v ́i nhau 13 Thí dụ C.5.4: Thời kỳ 1: (1946 -1954) ; Thời kỳ 2 (1955 – 1963) V ́i: Y – tiết kiệm, X thu nhập Y1 0.36 0.21 0.08 0.2 0.1 0.12 0.41 0.5 0.43 X1 8.8 9.4 10 10.6 11 11.9 12.7 13.5 14.3 Y2 0.59 0.9 0.95 0.82 1.04 1.53 1.94... Y1,2 = -1,082 + 0,117845X RSS 1,2= 0,5722266 RSS(1+2) = 0,13965+0,19312= 0,33277 (0,57722266  0,33277) / 2 F0   5,037 0,33277 / (9  9  4) F 0,05;(2,14) = 3,74 F0>F tới hạn  bác bỏ giả thiết cho rằng HQ Y1 và Y2 như nhau Nghĩa là hàm tiết kiệm ở 2 thời kỳ khác nhau có ý nghĩa thống kê 15 Bài tập 1 Y 15 15 16 16 17 17 18 18 19 20 X 5 5 4 4 3 4 4 3 3 2 Z 1 1 1 0 1 1 0 1 0 1 Y . src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABaAAAAQ4CAIAAABwgOwFAAAACXBIWXMAABYlAAAWJQFJUiTwAAAgAElEQVR42uzdvWtce5su6LukklRSlSpypmQCBZU4tHM7M0iZA6fGBoMxwhtGOBkUNJyoOzr/yAQzYWMwxoHxJxhsIxpsMD44cNTqZk59rKoJ3O/ud7/+lFUfa626rqihu7dKd62qrd/Ns39PYzKZBAAAAKDKVkQAAAAAVF1TBAAAUBaTIuNPGb7I4HkmJ+nczeqOVAB+RcN/ogIAAAs2PknxPoPHGT75x/ /V1 o2sX5QQwE8pOAAAYEGKjxkdp/8w448/+j9bv5zNq2msCgzgBxQcAAAwR5N+RscZvs7g/in +v5 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/V3 AMX+X/+78NawAAAEAFrF3I1nVXcvxp5b//x9X/I5MTiQAAAEAFDJ/k5H9k7CD/X/76n6iMT3LyT9ajAAAAQEWO9d20b7mSI9+4g0PHAQAAANWydSPrF5c8g29tURmf5N//T48HAAAAVMb65WxeXeYrOb6zJnb0b/mPf/Z4AAAAQGU0e9m6mZXt5fztv1NwRMcBAAAAlTvld9O5l9Vzy/irf7fgiI4DAAAAKqh9J2vnl+2X/mHBER0HAAAAVFBrPxtXlupKjp8VHNFxAAAAQAU1e2kfLE/H8QsFR3QcAAAAUMVDfzfbR0ty7eivFRzRcQAAAEA1dQ7T3K39b/nLBUd0HAAAAFBNrf209ur9K56m4IiOAwAAAKpp7UK2rtf4So5TFhzRcQAAAEA1reyk80ddr+Q4fcERHQcAAABUtAbopn2rlldy/FbBkeR//7/53/+PBwMAAACqZ/NaNi 7V7 Hf63YIjOg4AAACorPXL2bxapys5zlBwRMcBAAAAldXsZetmba7kOFvBER0HAAAAVFajm87drO7U4Vc5a8ERHQcAAABUWftO1s5X/ZeYRsERHQcAAABUWWs/G1cqfSXHlAqO6DgAAACgypq9tG+nsVHRlz+9giM6DgAAAKiyRjfbRxW9dnSqBUd0HAAAAFBxncM0dyv3qqddcETHAQAAABXX2k9rr1oveQYFR3QcAAAAUHHNXtoHFbp2dGUm/9SNK2n2PAwAAABQVaO3OfkfGZ9U5fXOZoIjyaTIf/7PjN56JAAAAKCqGt20b1XiSo6ZFRzRcQAAAEAtbF7LxqWSv8ZZFhzRcQAAAEAtrF/O5tUyX8kx44IjOg4AAACohWYvWzezsl3OVzf7giM6DgAAAKiFRjedu1ndKeNLm0fBEZxhVLIAACAASURBVB0HAAAA1MXWjaxfLNuLmlfBER0HAAAA1EVrPxtXSnUlxxwLjug4AAAAoC6avbRvp7FRkpcz34IjOg4AAACoi0Y3nXtZPVeK1zLvgiM6DgAAAKiRzmGauwt/FYsoOJJM+vn3/yuTf/cYAAAAQOW19tPaW+xLWFDBkWR8kpN/0nEAAABAHTR7aR8s8NrRxRUc0XEAAABAjTS62T7KyvZifvgiC47oOAAAAKBGGt20by3kSo5FFxzRcQAAAEC9bF7LxqU5/8wSFBzRcQAAAEC9rF3I1vV5XslRjoIjOg4AAACol2YvWzfndiXHSll+7ZXtbB+l0fUAAAAAQB0U/yuNrbn9tJUS/eY6DgAAAKiHLxtV5vifqKyU6/fXcQAAAEANdO7NeV/sSuki0HEAAABApXUOs3puzj9zpYxBrGync9fzAAAAANWzeS3N3fn/2JWSxrG6k86hpwIAAACqpLWfjUsL+ckr5Q2luavjAAAAgMpo9tLaW9QPXyl3NDoOAAAAqIJmL+2DBf78ldIHpOMAAACAcmt00749z6WwX1upQEw6DgAAACitRjfbR2lsLPZVrFQjLB0HAAAAlFP7Vla2F/4qViqTl44DAAAAyqZzuJClsF9bqVJqOg4AAAAoj9Z+SdqNVKzgiI4DAAAAymH98gKXwn5tpXoJ6jgAAABgwWfzXjavluoVrVQzx91s3fA4AQAAwAKs7KR9sNilsN94UVVNc/1iWvseKgAAAJirRjedP8rWbqTCBUeS1p6OAwAAAOaqc68MS2G/tlLtWHUcAAAAMDedw6yeK+dLW6l8uDoOAAAAmIOtG+VZCvu1lTpErOMAAACA2R6997N+scwvcKUuQes4AAAAYDaavbT2Sv4aV+oTt44DAAAApq7ZS/ug/C9zpVah6zgAAABgihrdtG+XcCns11bqFr2OAwAAAKai0c32URoblXixKzV8A3QcAAAAcHadu1nZrsqLXanne9Day9oFjyIAAAD8ps5hVncq9HpXavtObF1Ps+eBBAAAgFNr7ae5W62XXN+Co7Ga9oGOAwAAAE6ntV/+pbBfW6nzW6LjAAAAgFNp9rJxpYovfKXmb4yOAwAAAH7Ryk7aB5VYCvuN117/t0fHAQAAAD8/PnfT+aOi7UaSxmQyWYr3aVLkP/9nRm89sQAAAPAN3X+p0FLYr60sy/tkjgMAAAC+p3NY6XYjS1RwRMcBAAAA37J1o3JLYb+2slzvmY4DAAAA/l5rP+sXa/B7rCzdO6fjAAAAgC/WLqS 1V4 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/V3 AMX+X/+78NawAAAEAFrF3I1nVXcvxp5b//x9X/I5MTiQAAAEAFDJ/k5H9k7CD/X/76n6iMT3LyT9ajAAAAQEWO9d20b7mSI9+4g0PHAQAAANWydSPrF5c8g29tURmf5N//T48HAAAAVMb65WxeXeYrOb6zJnb0b/mPf/Z4AAAAQGU0e9m6mZXt5fztv1NwRMcBAAAAlTvld9O5l9Vzy/irf7fgiI4DAAAAKqh9J2vnl+2X/mHBER0HAAAAVFBrPxtXlupKjp8VHNFxAAAAQAU1e2kfLE/H8QsFR3QcAAAAUMVDfzfbR0ty7eivFRzRcQAAAEA1dQ7T3K39b/nLBUd0HAAAAFBNrf209ur9K56m4IiOAwAAAKpp7UK2rtf4So5TFhzRcQAAAEA1reyk80ddr+Q4fcERHQcAAABUtAbopn2rlldy/FbBkeR//7/53/+PBwMAAACqZ/NaNi 7V7 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 1V4 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