TV radio paper sales

230.1 37.8 69.2 22.1

44.5 39.3 45.1 10.4

17.2 45.9 69.3 9.3

151.5 41.3 58.5 18.5

180.8 10.8 58.4 12.9

8.7 48.9 75 7.2

57.5 32.8 23.5 11.8

120.2 19.6 11.6 13.2

8.6 2.1 1 4.8

199.8 2.6 21.2 10.6

66.1 5.8 24.2 8.6

214.7 24 4 17.4

23.8 35.1 65.9 9.2

97.5 7.6 7.2 9.7

204.1 32.9 46 19

195.4 47.7 52.9 22.4

67.8 36.6 114 12.5

281.4 39.6 55.8 24.4

69.2 20.5 18.3 11.3

147.3 23.9 19.1 14.6

218.4 27.7 53.4 18

237.4 5.1 23.5 12.5

13.2 15.9 49.6 5.6

228.3 16.9 26.2 15.5

62.3 12.6 18.3 9.7

262.9 3.5 19.5 12

142.9 29.3 12.6 15

240.1 16.7 22.9 15.9

248.8 27.1 22.9 18.9

70.6 16 40.8 10.5

292.9 28.3 43.2 21.4

112.9 17.4 38.6 11.9

97.2 1.5 30 9.6

265.6 20 0.3 17.4

95.7 1.4 7.4 9.5

290.7 4.1 8.5 12.8

266.9 43.8 5 25.4

74.7 49.4 45.7 14.7

43.1 26.7 35.1 10.1

228 37.7 32 21.5

202.5 22.3 31.6 16.6

177 33.4 38.7 17.1

293.6 27.7 1.8 20.7

206.9 8.4 26.4 12.9

25.1 25.7 43.3 8.5

175.1 22.5 31.5 14.9

89.7 9.9 35.7 10.6

239.9 41.5 18.5 23.2

227.2 15.8 49.9 14.8

66.9 11.7 36.8 9.7

199.8 3.1 34.6 11.4

100.4 9.6 3.6 10.7

216.4 41.7 39.6 22.6

182.6 46.2 58.7 21.2

262.7 28.8 15.9 20.2

198.9 49.4 60 23.7

7.3 28.1 41.4 5.5

136.2 19.2 16.6 13.2

210.8 49.6 37.7 23.8

210.7 29.5 9.3 18.4

53.5 2 21.4 8.1

261.3 42.7 54.7 24.2

239.3 15.5 27.3 15.7

102.7 29.6 8.4 14

131.1 42.8 28.9 18

69 9.3 0.9 9.3

31.5 24.6 2.2 9.5

139.3 14.5 10.2 13.4

237.4 27.5 11 18.9

216.8 43.9 27.2 22.3

199.1 30.6 38.7 18.3

109.8 14.3 31.7 12.4

26.8 33 19.3 8.8

129.4 5.7 31.3 11

213.4 24.6 13.1 17

16.9 43.7 89.4 8.7

27.5 1.6 20.7 6.9

120.5 28.5 14.2 14.2

5.4 29.9 9.4 5.3

116 7.7 23.1 11

76.4 26.7 22.3 11.8

239.8 4.1 36.9 12.3

75.3 20.3 32.5 11.3

68.4 44.5 35.6 13.6

213.5 43 33.8 21.7

193.2 18.4 65.7 15.2

76.3 27.5 16 12

110.7 40.6 63.2 16

88.3 25.5 73.4 12.9

109.8 47.8 51.4 16.7

134.3 4.9 9.3 11.2

28.6 1.5 33 7.3

217.7 33.5 59 19.4

250.9 36.5 72.3 22.2

107.4 14 10.9 11.5

163.3 31.6 52.9 16.9

197.6 3.5 5.9 11.7

184.9 21 22 15.5

289.7 42.3 51.2 25.4

135.2 41.7 45.9 17.2

222.4 4.3 49.8 11.7

296.4 36.3 100.9 23.8

280.2 10.1 21.4 14.8

187.9 17.2 17.9 14.7

238.2 34.3 5.3 20.7

137.9 46.4 59 19.2

25 11 29.7 7.2

90.4 0.3 23.2 8.7

13.1 0.4 25.6 5.3

255.4 26.9 5.5 19.8

225.8 8.2 56.5 13.4

241.7 38 23.2 21.8

175.7 15.4 2.4 14.1

209.6 20.6 10.7 15.9

78.2 46.8 34.5 14.6

75.1 35 52.7 12.6

139.2 14.3 25.6 12.2

76.4 0.8 14.8 9.4

125.7 36.9 79.2 15.9

19.4 16 22.3 6.6

141.3 26.8 46.2 15.5

18.8 21.7 50.4 7

224 2.4 15.6 11.6

123.1 34.6 12.4 15.2

229.5 32.3 74.2 19.7

87.2 11.8 25.9 10.6

7.8 38.9 50.6 6.6

80.2 0 9.2 8.8

220.3 49 3.2 24.7

59.6 12 43.1 9.7

0.7 39.6 8.7 1.6

265.2 2.9 43 12.7

8.4 27.2 2.1 5.7

219.8 33.5 45.1 19.6

36.9 38.6 65.6 10.8

48.3 47 8.5 11.6

25.6 39 9.3 9.5

273.7 28.9 59.7 20.8

43 25.9 20.5 9.6

184.9 43.9 1.7 20.7

73.4 17 12.9 10.9

193.7 35.4 75.6 19.2

220.5 33.2 37.9 20.1

104.6 5.7 34.4 10.4

96.2 14.8 38.9 11.4

140.3 1.9 9 10.3

240.1 7.3 8.7 13.2

243.2 49 44.3 25.4

38 40.3 11.9 10.9

44.7 25.8 20.6 10.1

280.7 13.9 37 16.1

121 8.4 48.7 11.6

197.6 23.3 14.2 16.6

171.3 39.7 37.7 19

187.8 21.1 9.5 15.6

4.1 11.6 5.7 3.2

93.9 43.5 50.5 15.3

149.8 1.3 24.3 10.1

11.7 36.9 45.2 7.3

131.7 18.4 34.6 12.9

172.5 18.1 30.7 14.4

85.7 35.8 49.3 13.3

188.4 18.1 25.6 14.9

163.5 36.8 7.4 18

117.2 14.7 5.4 11.9

234.5 3.4 84.8 11.9

17.9 37.6 21.6 8

206.8 5.2 19.4 12.2

215.4 23.6 57.6 17.1

284.3 10.6 6.4 15

50 11.6 18.4 8.4

164.5 20.9 47.4 14.5

19.6 20.1 17 7.6

168.4 7.1 12.8 11.7

222.4 3.4 13.1 11.5

276.9 48.9 41.8 27

248.4 30.2 20.3 20.2

170.2 7.8 35.2 11.7

276.7 2.3 23.7 11.8

165.6 10 17.6 12.6

156.6 2.6 8.3 10.5

218.5 5.4 27.4 12.2

56.2 5.7 29.7 8.7

287.6 43 71.8 26.2

253.8 21.3 30 17.6

205 45.1 19.6 22.6

139.5 2.1 26.6 10.3

191.1 28.7 18.2 17.3

286 13.9 3.7 15.9

18.7 12.1 23.4 6.7

39.5 41.1 5.8 10.8

75.5 10.8 6 9.9

17.2 4.1 31.6 5.9

166.8 42 3.6 19.6

149.7 35.6 6 17.3

38.2 3.7 13.8 7.6

94.2 4.9 8.1 9.7

177 9.3 6.4 12.8

283.6 42 66.2 25.5

232.1 8.6 8.7 13.4

Run regression analysis for above data and answer questions below:

After building your first model, model 1, which used TV advertising to explain variance in sales, you decide to look at the relationship between radio advertising and sales (model 2) and newspaper advertising and sales (model 3).

Q. 1.Based on the output from the model 2 and model 3 code, write in the appropriate regression equation for sales and radio and sales and newspaper.

Q2.Based on the adjusted R-squared from model 1, model 2, and model 3, which model explains more of the variance in sales?

Q3.What do the 2 additional residiual plots explain to you?

Q4.Which model is the best predictor of sales and why?