I am using faraway::choccake data, and I want to fit a linear model.
I have used the following code:
library(faraway)
attach(chocake)
choccake #to have a sense of the data
choccake.lm<-lm(breakang~recipe+batch+temp,data=choccake)
summary(choccake.lm)
I have fitted linear model using 'lm' in R before too. But, here the output of summary(choccake.lm) looks a little different.
Here is the output (I'm attaching the choccake data too).
> choccake
recipe batch temp breakang
1 1 1 175 42
2 1 1 185 46
3 1 1 195 47
4 1 1 205 39
5 1 1 215 53
6 1 1 225 42
7 1 2 175 47
8 1 2 185 29
9 1 2 195 35
10 1 2 205 47
11 1 2 215 57
12 1 2 225 45
13 1 3 175 32
14 1 3 185 32
15 1 3 195 37
16 1 3 205 43
17 1 3 215 45
18 1 3 225 45
19 1 4 175 26
20 1 4 185 32
21 1 4 195 35
22 1 4 205 24
23 1 4 215 39
24 1 4 225 26
25 1 5 175 28
26 1 5 185 30
27 1 5 195 31
28 1 5 205 37
29 1 5 215 41
30 1 5 225 47
31 1 6 175 24
32 1 6 185 22
33 1 6 195 22
34 1 6 205 29
35 1 6 215 35
36 1 6 225 26
37 1 7 175 26
38 1 7 185 23
39 1 7 195 25
40 1 7 205 27
41 1 7 215 33
42 1 7 225 35
43 1 8 175 24
44 1 8 185 33
45 1 8 195 23
46 1 8 205 32
47 1 8 215 31
48 1 8 225 34
49 1 9 175 24
50 1 9 185 27
51 1 9 195 28
52 1 9 205 33
53 1 9 215 34
54 1 9 225 23
55 1 10 175 24
56 1 10 185 33
57 1 10 195 27
58 1 10 205 31
59 1 10 215 30
60 1 10 225 33
61 1 11 175 33
62 1 11 185 39
63 1 11 195 33
64 1 11 205 28
65 1 11 215 33
66 1 11 225 30
67 1 12 175 28
68 1 12 185 31
69 1 12 195 27
70 1 12 205 39
71 1 12 215 35
72 1 12 225 43
73 1 13 175 29
74 1 13 185 28
75 1 13 195 31
76 1 13 205 29
77 1 13 215 37
78 1 13 225 33
79 1 14 175 24
80 1 14 185 40
81 1 14 195 29
82 1 14 205 40
83 1 14 215 40
84 1 14 225 31
85 1 15 175 26
86 1 15 185 28
87 1 15 195 32
88 1 15 205 25
89 1 15 215 37
90 1 15 225 33
91 2 1 175 39
92 2 1 185 46
93 2 1 195 51
94 2 1 205 49
95 2 1 215 55
96 2 1 225 42
97 2 2 175 35
98 2 2 185 46
99 2 2 195 47
100 2 2 205 39
101 2 2 215 52
102 2 2 225 61
103 2 3 175 34
104 2 3 185 30
105 2 3 195 42
106 2 3 205 35
107 2 3 215 42
108 2 3 225 35
109 2 4 175 25
110 2 4 185 26
111 2 4 195 28
112 2 4 205 46
113 2 4 215 37
114 2 4 225 37
115 2 5 175 31
116 2 5 185 30
117 2 5 195 29
118 2 5 205 35
119 2 5 215 40
120 2 5 225 36
121 2 6 175 24
122 2 6 185 29
123 2 6 195 29
124 2 6 205 29
125 2 6 215 24
126 2 6 225 35
127 2 7 175 22
128 2 7 185 25
129 2 7 195 26
130 2 7 205 26
131 2 7 215 29
132 2 7 225 36
133 2 8 175 26
134 2 8 185 23
135 2 8 195 24
136 2 8 205 31
137 2 8 215 27
138 2 8 225 37
139 2 9 175 27
140 2 9 185 26
141 2 9 195 32
142 2 9 205 28
143 2 9 215 32
144 2 9 225 33
145 2 10 175 21
146 2 10 185 24
147 2 10 195 24
148 2 10 205 27
149 2 10 215 37
150 2 10 225 30
151 2 11 175 20
152 2 11 185 27
153 2 11 195 33
154 2 11 205 31
155 2 11 215 28
156 2 11 225 33
157 2 12 175 23
158 2 12 185 28
159 2 12 195 31
160 2 12 205 34
161 2 12 215 31
162 2 12 225 29
163 2 13 175 32
164 2 13 185 35
165 2 13 195 30
166 2 13 205 27
167 2 13 215 35
168 2 13 225 30
169 2 14 175 23
170 2 14 185 25
171 2 14 195 22
172 2 14 205 19
173 2 14 215 21
174 2 14 225 35
175 2 15 175 21
176 2 15 185 21
177 2 15 195 28
178 2 15 205 26
179 2 15 215 27
180 2 15 225 20
181 3 1 175 46
182 3 1 185 44
183 3 1 195 45
184 3 1 205 46
185 3 1 215 48
186 3 1 225 63
187 3 2 175 43
188 3 2 185 43
189 3 2 195 43
190 3 2 205 46
191 3 2 215 47
192 3 2 225 58
193 3 3 175 33
194 3 3 185 24
195 3 3 195 40
196 3 3 205 37
197 3 3 215 41
198 3 3 225 38
199 3 4 175 38
200 3 4 185 41
201 3 4 195 38
202 3 4 205 30
203 3 4 215 36
204 3 4 225 35
205 3 5 175 21
206 3 5 185 25
207 3 5 195 31
208 3 5 205 35
209 3 5 215 33
210 3 5 225 23
211 3 6 175 24
212 3 6 185 33
213 3 6 195 30
214 3 6 205 30
215 3 6 215 37
216 3 6 225 35
217 3 7 175 20
218 3 7 185 21
219 3 7 195 31
220 3 7 205 24
221 3 7 215 30
222 3 7 225 33
223 3 8 175 24
224 3 8 185 23
225 3 8 195 21
226 3 8 205 24
227 3 8 215 21
228 3 8 225 35
229 3 9 175 24
230 3 9 185 18
231 3 9 195 21
232 3 9 205 26
233 3 9 215 28
234 3 9 225 28
235 3 10 175 26
236 3 10 185 28
237 3 10 195 27
238 3 10 205 27
239 3 10 215 35
240 3 10 225 35
241 3 11 175 28
242 3 11 185 25
243 3 11 195 26
244 3 11 205 25
245 3 11 215 38
246 3 11 225 28
247 3 12 175 24
248 3 12 185 30
249 3 12 195 28
250 3 12 205 35
251 3 12 215 33
252 3 12 225 28
253 3 13 175 28
254 3 13 185 29
255 3 13 195 43
256 3 13 205 28
257 3 13 215 33
258 3 13 225 37
259 3 14 175 19
260 3 14 185 22
261 3 14 195 27
262 3 14 205 25
263 3 14 215 25
264 3 14 225 35
265 3 15 175 21
266 3 15 185 28
267 3 15 195 25
268 3 15 205 25
269 3 15 215 31
270 3 15 225 25
choccake.lm<-lm(breakang~recipe+batch+temp,data=choccake)
> summary(choccake.lm)
Call:
lm(formula = breakang ~ recipe + batch + temp, data = choccake)
Residuals:
Min 1Q Median 3Q Max
-15.1851 -2.5682 -0.0419 2.7553 13.4816
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 16.22698 3.63640 4.462 1.22e-05 ***
recipe2 -1.47778 0.71744 -2.060 0.0404 *
recipe3 -1.52222 0.71744 -2.122 0.0348 *
batch2 -1.27778 1.60424 -0.796 0.4265
batch3 -9.88889 1.60424 -6.164 2.79e-09 ***
batch4 -13.55556 1.60424 -8.450 2.36e-15 ***
batch5 -14.44444 1.60424 -9.004 < 2e-16 ***
batch6 -18.11111 1.60424 -11.289 < 2e-16 ***
batch7 -19.50000 1.60424 -12.155 < 2e-16 ***
batch8 -19.44444 1.60424 -12.121 < 2e-16 ***
batch9 -19.50000 1.60424 -12.155 < 2e-16 ***
batch10 -18.00000 1.60424 -11.220 < 2e-16 ***
batch11 -16.94444 1.60424 -10.562 < 2e-16 ***
batch12 -15.88889 1.60424 -9.904 < 2e-16 ***
batch13 -14.94444 1.60424 -9.316 < 2e-16 ***
batch14 -18.94444 1.60424 -11.809 < 2e-16 ***
batch15 -20.22222 1.60424 -12.605 < 2e-16 ***
temp 0.15803 0.01715 9.215 < 2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 4.813 on 252 degrees of freedom
Multiple R-squared: 0.6783, Adjusted R-squared: 0.6566
F-statistic: 31.25 on 17 and 252 DF, p-value: < 2.2e-16
My questions:
- the variables are 'recipe', 'batch' and 'temp'..then why for different values of recipe and batch it's showing different coefficient? it seems from the result that there are 17 dependent variables.
- why there's no mention of recipe1 and batch1?
- is it by any chance computing for several different regression lines?
