Question

Fit your best model to the following data. I would recommend studying the data and then trying to fit it.
Y X1 X2 X3 X4 X5
12229.31 101.51 77.44 7.32 122.08 51.45
19218.63 109.89 99.24 7.83 119.57 54.4
2579.63 95.75 103.61 4.68 125.69 53.35
7780.87 112.54 128.57 6.78 118.16 56.02
2135.14 108 116.21 4.18 120.68 48.99
1719.99 114.41 112.48 3.09 123.92 58.45
4538.07 123.96 98.62 6.1 122.83 57.47
3243.55 96.29 96.24 5.33 121.36 43.93
6983.13 90.04 121.44 6.57 121.96 47.19
3235.18 91.7 61.63 5.39 120.02 47.9
2103.12 108.73 120.02 4.12 122.03 56.04
2000.89 93.88 122.2 2.35 120.39 42.25
18954.66 89.34 92.37 7.8 123.52 50.91
2086.63 104.08 117.3 3.89 121.24 52.49
3204.28 88.42 69.43 5.32 123.13 45.86
1822.59 105.95 115.24 2.75 124.01 49.56
2390.57 85.29 126.99 3.75 120.65 54.22
4338.25 138.88 118.28 6.11 122.1 63.37
2473.58 110.86 69.87 4.88 124.26 53.49
2596.05 89.8 116.02 4.5 118.81 49.45
2338.73 76.83 96.31 3.7 123.42 34.46
3569.73 95.71 86.47 5.55 122.14 47.51
2862.5 67.19 97.87 4.56 123.67 30.92
14147.04 69.71 90.53 7.45 124.9 30.95
1774.99 134.75 54.3 4.2 120.27 60.46
6220.95 65.01 133.29 6.28 125.55 27.01
2623.72 84.03 113.22 4.42 121.31 40.64
2346.63 121.21 95.38 4.84 121.71 58.26
2921.79 102.39 63.9 5.23 122.28 56.89
4350.55 92.65 66.3 5.93 119.75 54.95
1791.59 134.63 112.5 4.32 118.95 63.88
1940.6 137.34 109.26 4.62 117.28 76.68
3378.7 110.87 79.93 5.56 123.11 65.38
5624.47 87.26 82.34 6.29 124.58 47.06
1664.26 116.01 88.31 3.06 120.2 58.95
3183.2 106.05 82.26 5.41 121.43 49.96
2002.1 76.21 50.14 3.47 118.82 42.44
2184.77 91.38 81.27 4.04 122.16 52.77
2072.61 96.31 70.94 3.99 122.8 57.88
3020.82 76.38 70.55 5.08 121.89 32.03

Answer 1

The regression analysis is:

Removing the highly insignificant variable, we get:

Removing the highly insignificant variable, we get:

Removing the highly insignificant variable, we get:

The best model is:

y = -8,508.8639 + 2,570.5312*X3

	r²	0.658
	r	0.811
	Std. Error	2563.182
	n	40
	k	1
	Dep. Var.	Y
ANOVA table
Source	SS	df	MS	F	p-value
Regression	47,93,81,671.5150	1	47,93,81,671.5150	72.97	2.25E-10
Residual	24,96,56,258.1865	38	65,69,901.5312
Total	72,90,37,929.7015	39
Regression output				confidence interval
variables	coefficients	std. error	t (df=38)	p-value	95% lower	95% upper
Intercept	-8,508.8639
X3	2,570.5312	300.9273	8.542	2.25E-10	1,961.3357	3,179.7266