Computer Programming                                                                                   Curvefit Data

n = 3

xi:  3   5   4   =>   3   4   5
yi:  7   2   6   =>   2   6   7

?x = 12      ?y = 15      ?x2 = 50      ?y2 = 89      ?xy =55

_                 _                __         _          __         _           __        _
x = 4           y = 5         ?x2 = 16.6  ????????y2 = 29.6          xy =18.3

x median = 4			y median = 6

No x mode       	        	No y mode

x range = 2			y range = 5
                      _                                                _
x variance = .6			y variance = 4.6

sx = .81649658092		sy = 2.1602468995

zx1 = -1.2247448714		zy1 = .92582009977
zx2 = 1.2247448714		zy2 = -1.3887301497
 zx3 = 0				zy3 = .46291004989

r = -.9449118252

m = -2.5

Function							Least-squares fit

Linear: y = -2.5 x + 15					1.5

Exponential: y = 5.3649109468 * 5.3452248382 x		4.1662427650

Power:  y = 110.00741656 * x –2.3619962645			5.0549795591

Computer Programming                                                                                   Curvefit Data

n = 4

xi:  3.5   2   4   2   =>   2   2   3.5   4
yi:  8      3   8   3   =>   3   3   8      8

?x = 11.5      ?y = 22      ?x2 = 36.25      ?y2 = 146      ?xy =72

_                     _                __                   __                    __
x = 2.875        y = 5.5      ?x2 = 9.0625  ??y2 = 36.5        xy =18

x median = 2.75		y median = 5.5

x mode = 2               		y modes = 3 and 8

x range = 2			y range = 5

x variance = .796875		y variance = 6.25

sx = .89267855357		sy = 2.5

zx1 = .70014004201		zy1 = 1
zx2 = -.98019605882		zy2 = -1
zx3 = 1.2602520756		zy3 = 1
zx4 = -.98019605882		zy4 = -1

r = .98019605882

m = 2.7450980392

y = 2.7450980392 x – 2.3921568627

Function							Least-squares fit

Linear: y = 2.7450980392 x – 2.3921568627			0.98039215687

Exponential: y = 1.0417013095 * 1.7134253436 x		2.2657566282

Power:  y = 1.0494303705 * x 1.5310755640			1.3195492675