Yi = B0 + B1 X1 +B2 X2 + B3 X3 +e

◦ where each of the Betas estimate the effect of one independent variable.

This allows the regression to "control" for each of the other factors simultaneously◦ e.g., control for exercise, eating habits, AND fish

consumption on heart attacks.

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Coefficientsa

56.730 75.172 .755 .455

1.626 .791 .319 2.056 .047

8.E-02 .983 .013 .080 .937

.949 .656 .235 1.446 .156

(Constant)

EXAM_1

EXAM_2

REVIEW_1

Model1

BStd.Error

UnstandardizedCoefficients

Beta

StandardizedCoefficients

t Sig.

Dependent Variable: TOTALa.

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Model

Unstandardized CoefficientsStandardized Coefficients t Sig.

B Std. Error Beta B Std. Error1 (Constant) 1.872 414.389 .005 .997

Quiz1 -1.968 6.790 -.169 -.290 .779

Quiz2 1.210 5.805 .095 .209 .840

Quiz3 -3.165 14.973 -.192 -.211 .838

Quiz4 3.584 8.857 .252 .405 .696

Quiz5 7.511 18.768 .473 .400 .699

Proj1 1.249 5.050 .106 .247 .811

Part1 1.209 19.745 .727 .061 .953

Quiz6 -4.481 13.304 -2.212 -.337 .745

Quiz7 6.552 18.152 3.298 .361 .727

Quiz8 -2.229 8.059 -.947 -.277 .789

Proj2 -.800 3.431 -.091 -.233 .821

Quiz9 -4.854 10.021 -2.292 -.484 .641

Part2 1.778 16.205 1.043 .110 .915

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Model

Unstandardized CoefficientsStandardized Coefficients t Sig.

B Std. Error Beta B Std. Error1 (Constant)

59.229 24.653 2.403 .025

QUIZ

-1.356 .311 -.666 -4.363 .000

REST

.466 .430 .165 1.083 .290

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