Differences

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--- multiple_regression_exercise [2021/12/03 01:50] – [개인과제 2] hkimscil
+++ multiple_regression_exercise [2021/12/07 08:11] – [추가 설명 2] hkimscil
@@ Line 389: / Line 389: @@
 아래는 설명을 하지 않고 코드만 적었었는데 이는 아래 둘의 model이 동일한 것임을 보여주기 위한 것입니다.
 <code>
-lm.2 <- lm(Sales ~ Advertising:ShelveLoc, data = Carseats) ------- (1)
+lm.2 <- lm(Sales ~ Advertising:ShelveLoc, data = Carseats) # ------- (1)
-lm.1 <- lm(Sales ~ Advertising + Advertising:ShelveLoc, data = Carseats) ------- (2)
+lm.1 <- lm(Sales ~ Advertising + Advertising:ShelveLoc, data = Carseats) # ------- (2)
 </code>
@@ Line 469: / Line 469: @@
 Coefficients:
                             Estimate Std. Error t value Pr(>|t|)
-(Intercept)                  5.01234    0.31932  15.697  < 2e-16 ***       (1)
+(Intercept)                  5.01234    0.31932  15.697  < 2e-16 ***    # (1)
-ShelveLocGood                4.43573    0.48146   9.213  < 2e-16 ***       (2)
+ShelveLocGood                4.43573    0.48146   9.213  < 2e-16 ***    # (2)
-ShelveLocMedium              1.59511    0.38378   4.156 3.97e-05 ***       (3)
+ShelveLocMedium              1.59511    0.38378   4.156 3.97e-05 ***    # (3)
-ShelveLocBad:Advertising     0.08210    0.03570   2.300  0.02198 *         (4)
+ShelveLocBad:Advertising     0.08210    0.03570   2.300  0.02198 *      # (4)
-ShelveLocGood:Advertising    0.10417    0.03607   2.888  0.00409 **        (5)
+ShelveLocGood:Advertising    0.10417    0.03607   2.888  0.00409 **     # (5)
-ShelveLocMedium:Advertising  0.10692    0.02280   4.689 3.78e-06 ***       (6)
+ShelveLocMedium:Advertising  0.10692    0.02280   4.689 3.78e-06 ***    # (6)
 ---
 Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1