{"id":10818,"date":"2026-09-22T06:00:00","date_gmt":"2026-09-21T21:00:00","guid":{"rendered":"https:\/\/triumphmind.com\/cfa\/2026\/09\/22\/cfa-l2-quants-lm1\/"},"modified":"2026-09-22T07:05:18","modified_gmt":"2026-09-21T22:05:18","slug":"cfa-l2-quants-lm1","status":"publish","type":"post","link":"https:\/\/triumphmind.com\/cfa\/2026\/09\/22\/cfa-l2-quants-lm1\/","title":{"rendered":"\u3010CFA\u00ae\ufe0e L2 Quants LM1\u3011Basics of Multiple Regression and Underlying Assumptions \u3092\u8981\u70b9\u89e3\u8aac\uff5c\u91cd\u56de\u5e30\u30e2\u30c7\u30eb\u30fb\u504f\u56de\u5e30\u4fc2\u6570\u30fb5\u3064\u306e\u524d\u63d0\u6761\u4ef6\u30fb\u6b8b\u5dee\u30d7\u30ed\u30c3\u30c8"},"content":{"rendered":"<style>\n.cfalm-los{counter-reset:los;list-style:none;padding:0!important;margin:1em 0!important}\n.cfalm-los li{border:1px solid #d5d9e3;border-left:4px solid #172152;border-radius:4px;padding:.8em 1em!important;margin:0 0 .8em!important;background:#fff}\n.cfalm-los li::before{display:none!important;content:none!important}\n.cfalm-los .ja{display:block;font-weight:bold;color:#172152;line-height:1.6}\n.cfalm-los .en{display:block;font-size:.85em;color:#667;margin-top:.3em;line-height:1.5;word-break:normal!important;overflow-wrap:anywhere}\n.cfalm-sum{background:#f6f7fb;border-radius:6px;padding:1em 1.2em!important;margin:1em 0!important;list-style:none!important}\n.cfalm-sum li{position:relative;margin:.4em 0!important;padding:0 0 0 1.1em!important;line-height:1.7;list-style:none!important}.cfalm-sum li::before{content:\"\"!important;display:block!important;position:absolute!important;left:0!important;top:.7em!important;width:6px!important;height:6px!important;border-radius:50%!important;background:#172152!important;border:none!important;transform:none!important}\n.cfalm-f{background:#f6f7fb;border-left:4px solid #172152;padding:.7em 1em;margin:.8em 0;font-family:\"Menlo\",\"Consolas\",monospace;font-size:.95em;overflow-x:auto}\n.cfalm-nav{background:#f6f7fb;padding:1em 1.2em;border-radius:6px;margin:1em 0;word-break:normal;overflow-wrap:anywhere}\n<\/style>\n<div class=\"box05\">\n<p>Learning Module 1\u300cBasics of Multiple Regression and Underlying Assumptions\uff08\u91cd\u56de\u5e30\u306e\u57fa\u790e\u3068\u524d\u63d0\u6761\u4ef6\uff09\u300d\u306f\u3001\u91cd\u56de\u5e30\u5206\u6790\u3067\u6271\u3048\u308b\u6295\u8cc7\u4e0a\u306e\u554f\u984c\u3068\u5206\u6790\u30d7\u30ed\u30bb\u30b9\u3001\u91cd\u56de\u5e30\u30e2\u30c7\u30eb\u306e\u7acb\u3066\u65b9\u3068\u56de\u5e30\u4fc2\u6570\uff08\u504f\u56de\u5e30\u4fc2\u6570\uff09\u306e\u89e3\u91c8\u3001\u305d\u3057\u3066\u91cd\u56de\u5e30\u306e5\u3064\u306e\u524d\u63d0\u6761\u4ef6\u3068\u6b8b\u5dee\u30d7\u30ed\u30c3\u30c8\u306b\u3088\u308b\u9055\u53cd\u306e\u898b\u3064\u3051\u65b9\u3092\u6271\u3046\u5358\u5143\u3067\u3059\u3002<\/p>\n<p>\u672c\u8a18\u4e8b\u3067\u306f\u3001\u6700\u65b0\u7248\u30ab\u30ea\u30ad\u30e5\u30e9\u30e0\u306eLOS\uff08Learning Outcome Statement\uff09\u3068\u3001\u3053\u306e\u5358\u5143\u306e\u91cd\u8981\u8ad6\u70b9\u3092\u65e5\u672c\u8a9e\u3067\u6574\u7406\u3057\u307e\u3057\u305f\u3002<\/p>\n<\/div>\n<h2>LM1\u306eLOS\uff08\u5b66\u7fd2\u76ee\u6a19\uff09<\/h2>\n<p>LOS\u306f\u3001\u3053\u306e\u5358\u5143\u3067\u300c\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u308b\u3079\u304d\u3053\u3068\u300d\u3068\u3057\u3066\u793a\u3055\u308c\u3066\u3044\u308b\u5b66\u7fd2\u76ee\u6a19\u3067\u3059\u3002LM1\u306b\u306f3\u3064\u306eLOS\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n<ol class=\"cfalm-los\">\n<li><span class=\"ja\">LOS 1\uff1a\u91cd\u56de\u5e30\u5206\u6790\u304c\u6271\u3046\u6295\u8cc7\u4e0a\u306e\u554f\u984c\u306e\u7a2e\u985e\u3068\u3001\u56de\u5e30\u5206\u6790\u306e\u30d7\u30ed\u30bb\u30b9\u3092\u8aac\u660e\u3059\u308b<\/span><span class=\"en\">describe the types of investment problems addressed by multiple linear regression and the regression process<\/span><\/li>\n<li><span class=\"ja\">LOS 2\uff1a\u91cd\u56de\u5e30\u30e2\u30c7\u30eb\u3092\u5b9a\u5f0f\u5316\u3057\u3001\u5f93\u5c5e\u5909\u6570\u3068\u8907\u6570\u306e\u72ec\u7acb\u5909\u6570\u306e\u95a2\u4fc2\u3092\u8aac\u660e\u3057\u3001\u63a8\u5b9a\u3055\u308c\u305f\u56de\u5e30\u4fc2\u6570\u3092\u89e3\u91c8\u3059\u308b<\/span><span class=\"en\">formulate a multiple linear regression model, describe the relation between the dependent variable and several independent variables, and interpret estimated regression coefficients<\/span><\/li>\n<li><span class=\"ja\">LOS 3\uff1a\u91cd\u56de\u5e30\u30e2\u30c7\u30eb\u306e\u524d\u63d0\u6761\u4ef6\u3092\u8aac\u660e\u3057\u3001\u524d\u63d0\u6761\u4ef6\u306e\u9055\u53cd\u306e\u53ef\u80fd\u6027\u3092\u793a\u3059\u6b8b\u5dee\u30d7\u30ed\u30c3\u30c8\u3092\u89e3\u91c8\u3059\u308b<\/span><span class=\"en\">explain the assumptions underlying a multiple linear regression model and interpret residual plots indicating potential violations of these assumptions<\/span><\/li>\n<\/ol>\n<h2>LM1\u306e\u307e\u3068\u3081<\/h2>\n<p>\u3053\u306e\u5358\u5143\u306e\u8981\u70b9\u3092\u307e\u3068\u3081\u308b\u3068\u3001\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002<\/p>\n<ul class=\"cfalm-sum\">\n<li>\u91cd\u56de\u5e30\u306f\u30011\u3064\u306e\u5f93\u5c5e\u5909\u6570\u30682\u3064\u4ee5\u4e0a\u306e\u72ec\u7acb\u5909\u6570\u306e\u7dda\u5f62\u95a2\u4fc2\u3092\u30e2\u30c7\u30eb\u5316\u3059\u308b\u624b\u6cd5<\/li>\n<li>\u5b9f\u52d9\u3067\u306e\u7528\u9014\u306f\u3001\u91d1\u878d\u5909\u6570\u9593\u306e\u95a2\u4fc2\u306e\u8aac\u660e\u3001\u65e2\u5b58\u7406\u8ad6\u306e\u691c\u8a3c\u3001\u4e88\u6e2c\u306e3\u3064<\/li>\n<li>\u56de\u5e30\u5206\u6790\u306e\u30d7\u30ed\u30bb\u30b9\u3067\u306f\u3001\u5f93\u5c5e\u5909\u6570\u30fb\u72ec\u7acb\u5909\u6570\u306e\u7279\u5b9a\u3001\u30e2\u30c7\u30eb\u306e\u9078\u629e\u3001\u524d\u63d0\u6761\u4ef6\u306e\u78ba\u8a8d\u3001\u5f53\u3066\u306f\u307e\u308a\u306e\u691c\u8a0e\u3001\u5fc5\u8981\u306a\u4fee\u6b63\u3068\u3044\u3063\u305f\u5224\u65ad\u3092\u9806\u306b\u884c\u3046<\/li>\n<li>\u30e2\u30c7\u30eb\u306f Yi = b0 + b1X1i + \u2026 + bkXki + \u03b5i \u3067\u8868\u3055\u308c\u3001n \u500b\u306e\u89b3\u6e2c\u5024\u304b\u3089\u63a8\u5b9a\u3059\u308b<\/li>\n<li>\u5207\u7247 b0 \u306f\u3059\u3079\u3066\u306e\u72ec\u7acb\u5909\u6570\u304c\u30bc\u30ed\u306e\u3068\u304d\u306e Y \u306e\u671f\u5f85\u5024\u3002\u50be\u304d bj \u306f\u4ed6\u306e\u72ec\u7acb\u5909\u6570\u3092\u4e00\u5b9a\u3068\u3057\u305f\u3068\u304d\u306e Xj \u306e Y \u3078\u306e\u5f71\u97ff\uff08\u504f\u56de\u5e30\u4fc2\u6570\uff09<\/li>\n<li>\u524d\u63d0\u6761\u4ef6\u306f\u3001\u7dda\u5f62\u6027\u30fb\u7b49\u5206\u6563\u6027\u30fb\u8aa4\u5dee\u9805\u306e\u72ec\u7acb\u6027\u30fb\u6b63\u898f\u6027\u30fb\u72ec\u7acb\u5909\u6570\u9593\u306e\u72ec\u7acb\u6027\u306e5\u3064<\/li>\n<li>\u6563\u5e03\u56f3\u306f\u975e\u7dda\u5f62\u95a2\u4fc2\u306e\u767a\u898b\u306b\u3001\u6b8b\u5dee\u30d7\u30ed\u30c3\u30c8\u306f\u4e0d\u5747\u4e00\u5206\u6563\u3084\u8aa4\u5dee\u306e\u76f8\u95a2\u306e\u767a\u898b\u306b\u5f79\u7acb\u3064<\/li>\n<\/ul>\n<p>\u4ee5\u4e0b\u3001LOS\u3054\u3068\u306b\u91cd\u8981\u8ad6\u70b9\u3092\u6574\u7406\u3057\u307e\u3059\u3002<\/p>\n<h3>LOS 1\uff1a\u91cd\u56de\u5e30\u304c\u6271\u3046\u554f\u984c\u3068\u56de\u5e30\u5206\u6790\u306e\u30d7\u30ed\u30bb\u30b9<\/h3>\n<p>\u91cd\u56de\u5e30\u306f\u3001\u3042\u308b\u5909\u6570\uff08\u5f93\u5c5e\u5909\u6570\uff09\u306e\u52d5\u304d\u3092<strong>\u8907\u6570\u306e\u8aac\u660e\u8981\u56e0\uff08\u72ec\u7acb\u5909\u6570\uff09<\/strong>\u3067\u8aac\u660e\u30fb\u4e88\u6e2c\u3059\u308b\u305f\u3081\u306e\u624b\u6cd5\u3067\u3059\u3002\u5909\u6570\u306e\u9078\u629e\u304b\u3089\u30e2\u30c7\u30eb\u306e\u9078\u5b9a\u3001\u524d\u63d0\u6761\u4ef6\u306e\u78ba\u8a8d\u3001\u5f53\u3066\u306f\u307e\u308a\u306e\u8a55\u4fa1\u3001\u4fee\u6b63\u307e\u3067\u306e\u4e00\u9023\u306e\u6d41\u308c\u3068\u3057\u3066\u7406\u89e3\u3059\u308b\u3053\u3068\u304c\u6c42\u3081\u3089\u308c\u307e\u3059\u3002<\/p>\n<ul>\n<li>\u7528\u9014\uff1a\u91d1\u878d\u5909\u6570\u9593\u306e\u95a2\u4fc2\u306e\u8aac\u660e\u3001\u7406\u8ad6\uff08\u30d5\u30a1\u30af\u30bf\u30fc\u30fb\u30e2\u30c7\u30eb\u306a\u3069\uff09\u306e\u691c\u8a3c\u3001\u4e88\u6e2c<\/li>\n<li>\u5f93\u5c5e\u5909\u6570\u304c\u9023\u7d9a\u306a\u3089\u7dda\u5f62\u56de\u5e30\u3001\u4e8c\u5024\uff08\u306f\u3044\u30fb\u3044\u3044\u3048\uff09\u306a\u3089\u30ed\u30b8\u30b9\u30c6\u30a3\u30c3\u30af\u56de\u5e30<\/li>\n<li>\u30d7\u30ed\u30bb\u30b9\uff1a\u5909\u6570\u306e\u7279\u5b9a\u2192\u30e2\u30c7\u30eb\u9078\u629e\u2192\u524d\u63d0\u6761\u4ef6\u306e\u78ba\u8a8d\u2192\u5f53\u3066\u306f\u307e\u308a\u306e\u8a55\u4fa1\u2192\u5fc5\u8981\u306a\u4fee\u6b63<\/li>\n<li>\u524d\u63d0\u304c\u6e80\u305f\u3055\u308c\u306a\u3044\u5834\u5408\u306f\u30e2\u30c7\u30eb\u306e\u4fee\u6b63\u3084\u5225\u624b\u6cd5\u306e\u691c\u8a0e\u3078<\/li>\n<\/ul>\n<h3>LOS 2\uff1a\u91cd\u56de\u5e30\u30e2\u30c7\u30eb\u306e\u5b9a\u5f0f\u5316\u3068\u4fc2\u6570\u306e\u89e3\u91c8<\/h3>\n<p>\u91cd\u56de\u5e30\u30e2\u30c7\u30eb\u306f\u5207\u7247\u3068\u8907\u6570\u306e\u50be\u304d\u4fc2\u6570\u304b\u3089\u6210\u308a\u3001\u5404\u50be\u304d\u4fc2\u6570\u306f<strong>\u4ed6\u306e\u72ec\u7acb\u5909\u6570\u3092\u4e00\u5b9a\u306b\u4fdd\u3063\u305f\u3068\u304d\u306e<\/strong>\u305d\u306e\u5909\u65701\u5358\u4f4d\u306e\u5909\u5316\u306b\u5bfe\u3059\u308b\u5f93\u5c5e\u5909\u6570\u306e\u5909\u5316\u3092\u8868\u3057\u307e\u3059\u3002\u3053\u306e\u610f\u5473\u3067<strong>\u504f\u56de\u5e30\u4fc2\u6570\uff08partial regression coefficient\uff09<\/strong>\u3068\u547c\u3070\u308c\u307e\u3059\u3002<\/p>\n<ul>\n<li>\u5207\u7247 b0\uff1a\u3059\u3079\u3066\u306e\u72ec\u7acb\u5909\u6570\u304c\u30bc\u30ed\u306e\u3068\u304d\u306e Y \u306e\u671f\u5f85\u5024<\/li>\n<li>\u50be\u304d bj\uff1a\u4ed6\u306e\u5909\u6570\u4e00\u5b9a\u306e\u3082\u3068\u3067\u306e Xj \u306e1\u5358\u4f4d\u5909\u5316\u306b\u5bfe\u3059\u308b Y \u306e\u5909\u5316<\/li>\n<li>k \u500b\u306e\u72ec\u7acb\u5909\u6570\u306a\u3089\u63a8\u5b9a\u3059\u308b\u30d1\u30e9\u30e1\u30fc\u30bf\u306f k\uff0b1 \u500b<\/li>\n<li>\u5358\u56de\u5e30\u306e\u50be\u304d\u3068\u306f\u5024\u3082\u610f\u5473\u3082\u7570\u306a\u308a\u5f97\u308b\u70b9\u306b\u6ce8\u610f<\/li>\n<\/ul>\n<div class=\"cfalm-f\">Yi = b0 + b1X1i + b2X2i + \u2026 + bkXki + \u03b5i<\/div>\n<h3>LOS 3\uff1a5\u3064\u306e\u524d\u63d0\u6761\u4ef6\u3068\u6b8b\u5dee\u30d7\u30ed\u30c3\u30c8<\/h3>\n<p>\u91cd\u56de\u5e30\u306e\u63a8\u5b9a\u7d50\u679c\u3084\u691c\u5b9a\u3092\u4fe1\u983c\u3059\u308b\u306b\u306f\u3001<strong>\u7dda\u5f62\u6027\u30fb\u7b49\u5206\u6563\u6027\u30fb\u8aa4\u5dee\u306e\u72ec\u7acb\u6027\u30fb\u6b63\u898f\u6027\u30fb\u72ec\u7acb\u5909\u6570\u9593\u306e\u72ec\u7acb\u6027<\/strong>\u306e5\u3064\u306e\u524d\u63d0\u304c\u6e80\u305f\u3055\u308c\u3066\u3044\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u524d\u63d0\u306e\u9055\u53cd\u306f\u3001\u6563\u5e03\u56f3\u3084\u6b8b\u5dee\u30d7\u30ed\u30c3\u30c8\u306a\u3069\u306e\u8a3a\u65ad\u56f3\u3067\u898b\u3064\u3051\u307e\u3059\u3002<\/p>\n<ul>\n<li>\u7dda\u5f62\u6027\uff1a\u5f93\u5c5e\u5909\u6570\u3068\u72ec\u7acb\u5909\u6570\u306e\u95a2\u4fc2\u304c\u7dda\u5f62<\/li>\n<li>\u7b49\u5206\u6563\u6027\uff1a\u8aa4\u5dee\u9805\u306e\u5206\u6563\u304c\u3059\u3079\u3066\u306e\u89b3\u6e2c\u5024\u3067\u4e00\u5b9a<\/li>\n<li>\u8aa4\u5dee\u306e\u72ec\u7acb\u6027\uff1a\u8aa4\u5dee\u9805\u3069\u3046\u3057\u304c\u7121\u76f8\u95a2<\/li>\n<li>\u6b63\u898f\u6027\uff1a\u8aa4\u5dee\u9805\u304c\u6b63\u898f\u5206\u5e03\u306b\u5f93\u3046\uff08Q-Q \u30d7\u30ed\u30c3\u30c8\u3067\u78ba\u8a8d\uff09<\/li>\n<li>\u72ec\u7acb\u5909\u6570\u9593\u306e\u72ec\u7acb\u6027\uff1a\u72ec\u7acb\u5909\u6570\u9593\u306b\u53b3\u5bc6\u306a\u7dda\u5f62\u95a2\u4fc2\u304c\u306a\u3044<\/li>\n<li>\u6b8b\u5dee\u306b\u6247\u5f62\u306e\u5e83\u304c\u308a\u3084\u30d1\u30bf\u30fc\u30f3\u304c\u3042\u308c\u3070\u4e0d\u5747\u4e00\u5206\u6563\u30fb\u7cfb\u5217\u76f8\u95a2\u306e\u7591\u3044<\/li>\n<\/ul>\n<h2>\u52b9\u7387\u3088\u304f\u5b66\u3076\u306b\u306f FA-Academy<\/h2>\n<p>CFA\u00ae\ufe0e\u306e\u5354\u4f1a\u30c6\u30ad\u30b9\u30c8\u306f\u82f1\u8a9e\u3067\u5206\u91cf\u3082\u591a\u304f\u30011\u3064\u3072\u3068\u3064\u306e\u5358\u5143\u3092\u82f1\u8a9e\u3060\u3051\u3067\u7406\u89e3\u3057\u3066\u3044\u304f\u306e\u306f\u5927\u304d\u306a\u8ca0\u62c5\u3067\u3059\u3002<\/p>\n<p>FA-Academy\uff08Financial Analyst Academy\uff09\u306f\u3001<strong>\u65e5\u672c\u8a9e\u3067\u5b66\u3079\u308b\u6570\u5c11\u306a\u3044CFA\u00ae\ufe0e\u8a66\u9a13\u30b5\u30dd\u30fc\u30c8<\/strong>\u3067\u3059\u3002\u3053\u308c\u307e\u3067 Level 1 \u304b\u3089 Level 3 \u307e\u3067\u591a\u304f\u306e\u5408\u683c\u8005\u3092\u8f29\u51fa\u3057\u3066\u304a\u308a\u3001\u5408\u683c\u8005\u306e\u65b9\u3005\u3068\u306e\u5bfe\u8ac7\u3082\u6570\u591a\u304f\u516c\u958b\u3057\u3066\u3044\u307e\u3059\u3002\u3069\u3093\u306a\u65b9\u304c\u3001\u3069\u306e\u3088\u3046\u306b\u5408\u683c\u3055\u308c\u305f\u306e\u304b\u306f<a href=\"https:\/\/triumphmind.com\/cfa\/category\/gokaku\/\" target=\"_blank\" rel=\"noopener\">\u5408\u683c\u8005\u5bfe\u8ac7\u30fb\u5408\u683c\u4f53\u9a13\u8ac7\u306e\u4e00\u89a7<\/a>\u304b\u3089\u3054\u89a7\u3044\u305f\u3060\u3051\u307e\u3059\u3002<\/p>\n<ul>\n<li><a href=\"https:\/\/triumphmind.com\/cfa\/level2movie\/\" target=\"_blank\" rel=\"noopener\">Level 2 \u65e5\u672c\u8a9e\u8981\u70b9\u96c6\u306e\u7121\u6599\u30b5\u30f3\u30d7\u30eb\u3092\u53d7\u3051\u53d6\u308b\uff087\u65e5\u9593\u30e1\u30fc\u30eb\u8b1b\u5ea7\uff09<\/a><\/li>\n<li><a href=\"https:\/\/timerex.net\/s\/cfa.tips.slack_2a23\/e72e883e\/\" target=\"_blank\" rel=\"noopener\">\u7121\u6599\u500b\u5225\u9762\u8ac7\u3092\u4e88\u7d04\u3059\u308b\uff08\u5b66\u7fd2\u8a08\u753b\u306e\u3054\u76f8\u8ac7\uff09<\/a><\/li>\n<li><a href=\"https:\/\/triumphmind.com\/cfa\/course\/\" target=\"_blank\" rel=\"noopener\">\u53d7\u8b1b\u6848\u5185\uff08\u30b3\u30fc\u30b9\u4e00\u89a7\u30fb\u53d7\u8b1b\u6599\uff09\u3092\u898b\u308b<\/a><\/li>\n<\/ul>\n<div class=\"cfalm-nav\">\u6b21\u306e\u5358\u5143\uff1a<a href=\"https:\/\/triumphmind.com\/cfa\/2026\/09\/22\/cfa-l2-quants-lm2\/\">LM2 Evaluating Regression Model Fit and Interpreting Model Results\uff08\u56de\u5e30\u30e2\u30c7\u30eb\u306e\u5f53\u3066\u306f\u307e\u308a\u3068\u7d50\u679c\u306e\u89e3\u91c8\uff09<\/a><br \/>\n\u5168\u4f53\u306e\u76ee\u6b21\uff1a<a href=\"https:\/\/triumphmind.com\/cfa\/cfa-curriculum\/#l2-quants\">CFA\u00ae\ufe0e \u5b66\u7fd2\u5185\u5bb9\u306e\u76ee\u6b21\uff08Level 2 Quantitative Methods\uff09<\/a><\/div>\n","protected":false},"excerpt":{"rendered":"<p>CFA\u00ae\ufe0e Level 2 Quantitative Methods LM1\u300cBasics of Multiple Regression and Underlying 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