Question:hey tutors, happy Thanksgiving!! please help me answer my following questions.

Question #1) Scatter plots are used to discover relationships between variables. Using the corresponding measurements of variable 1 and variable 2 in DATA below, plot variable 1 vs. variable 2 and describe the correlation between variable 1 and variable 2.

Variable 1 Variable 2

5.92418 16.01040

-2.15342 6.90096

-5.68710 3.20965

-2.35173 8.11837

9.13267 20.86393

8.84593 17.88436

0.60205 11.33976

4.30225 13.72104

-9.69073 0.22652

-6.81619 2.88607

7.00841 14.48358

4.48845 15.56499

3.06470 11.36857

-9.46731 1.14076

1.54090 12.95229

-4.20144 5.79307

6.11798 15.91570

9.94412 16.96745

1.32124 10.86254

-7.69106 1.10462

5.89874 15.93450

-0.72913 10.47150

8.39173 17.99690

-9.46846 0.72233

Question #2) correlation is used to discover relationships between variables. Evaluate the correlation between the variable in DATA belwo. what is the correlation?

variable 1 variable 2

-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

Question #3) You are required 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,

variable 1 variable 2

-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

Question #4) An important application of regression in manufacturing is the estimation of cost of production. Based on the DATA below from AJAX Widgets relating cost (Y) to volume (x), what is the cost of producing 600 WIDGETS?

Production Volume (units) Total Cost ($)

400 3430

450 4080

550 4878

600 4884

700 5913

750 6402

425 4273

475 4362

575 5089

625 5446

725 6017

775 6591