Instructions Regression - Assumption Regression - Assumptions Question 25 (4 points) You are required to setup a predictive equation involving variable 1 and variable 2. First, you plot the DATA to determine if linear regression applies. You decide Linear regression is not applicable because the point pattern is curvilinear (has a curve). Linear regression is not applicable because it appears that there are two linear patterns indicating that the data come from two populations. You need more information before deciding to use linear regression. The linear regression equation will be very useful because the points have a strong linear pattern. Linear regression is not useful because the points have no discernible pattern.
	variable1	variable2
	-1.60263	6.66630
	5.13511	22.39796
	6.36533	48.04439
	5.62218	33.73949
	-2.19935	13.13368
	6.44037	34.07411
	7.53576	57.43268
	6.84911	46.18391
	-0.96507	2.31758
	-7.97987	66.45126
	7.71148	60.12220
	8.00414	69.34776
	-1.84249	-8.58487
	-6.64529	35.44469
	3.52281	15.81326
	6.12823	42.51683
	-8.02429	63.53322
	1.93739	10.39306
	1.60250	-1.67370
	9.59542	92.44574
	0.97873	-2.22144
	7.61991	66.59948
	6.35683	35.62167
	4.60624	15.37388

Regression - Assumption Regression - Assumptions Question 25 (4 points) You are required to setup a predictive equation involving variable 1 and variable 2. First, you plot the DATA to determine if linear regression applies. You decide Linear regression is not applicable because the point pattern is curvilinear (has a curve). Linear regression is not applicable because it appears that there are two linear patterns indicating that the data come from two populations. You need more information before deciding to use linear regression. The linear regression equation will be very useful because the points have a strong linear pattern. Linear regression is not useful because the points have no discernible pattern