1) Your job needs you to setup a predictive equation involving variable 1 and variable 2. First you plot the data below to determine if linear regression applies. You decide: please see multiple choices and data below.

variable1 variable2

-0.21582 0.89369

0.56997 -0.72620

-0.54850 -0.09185

-0.12385 0.50086

0.06975 -0.73607

0.16327 0.88498

-0.72595 -0.27512

0.22500 0.62647

-0.40463 0.92432

0.67652 0.56368

-0.82322 0.73005

0.06747 -0.74824

0.74055 0.79412

-0.71577 -0.04509

-0.82231 -0.70951

-0.47603 0.01573

0.58094 0.51169

-0.58573 0.10376

0.19003 -0.90089

-0.49528 0.04767

0.93083 -0.16886

0.61389 -0.65529

-0.91742 0.25296

-0.60957 -0.24747

a) You need more information before deciding to use linear regression

b) Linear regression is not applicable because the point pattern is curvilinear (has a curve).

c) The linear regression equation will be very useful because the points have a strong linear pattern

d) Linear regression is not applicable because it appears that there are two linear patterns indicating that the data come from two populations.

e) Linear regression is not useful because the points have no discernible pattern.

2) An important application of regression in manufacturing is the estimation of cost of production. Based of the data below from Turner Widgets relating cost (Y) to volume (X) what is the cost per widget? Please see multiple choice answers and data below.

Hint: What is the regression equation? What do the regression constants mean? 1 widget is a production of volume of 1.

Production

Volume (units) Total Cost ($)

400 5424

450 5657

550 5759

600 7294

700 7583

750 8603

425 5311

475 6093

575 6662

625 7380

725 7784

775 8588

a) 8.75

b) 7054

c) 8.21

d) 7.38

e) None of the above are correct