Multiple Regression Analysis:

1. New Data Set

2. Input Data

3. Click over to Variable View

4. Name each variable (do not put spaces)

5. Label each variable

6. Assign a measure

a. Nominal

i. This is for things like names, store, gender, type of student, etc.

b. Scale

i. This is for weight, annual sales, square footage, things on a scale

7. Next go to Analyze Ã Regression Ã Linear

8. Insert Dependent Variable and Independent Variable

a. Dependent variable is what you are trying to find out

b. Independent variable is what is being manipulated

9. Select OK

10. Data will be put in the output screen

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.954a

.910

.893

978.44654

a. Predictors: (Constant), Square Footage, Number of Employees

ANOVAa

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

106209441.045

2

53104720.522

55.470

.000b

Residual

10530933.884

11

957357.626

Total

116740374.929

13

a. Dependent Variable: AnnualSales

b. Predictors: (Constant), Square Footage, Number of Employees

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

888.502

636.215

1.397

.190

Number of Employees

.442

11.907

.004

.037

.971

Square Footage

1.684

.171

.953

9.876

.000

a. Dependent Variable: AnnualSales

11. Write up the analysis

â€‹a. Define the dependent variable and the predictor (independent variable).

â€‹b. Discuss the test used (Multiple Regression)

c. R2 = .91 which means that 91% of annual sales is being predicted by BOTH the number of employees and square footage

d. F (df) = ________ , p ________ will tell us whether or not the multiple regression used to determine if the predictors affect the dependent variables was significant

â€‹i. F (2,13) = 55.47, p < .001 tells us that the multiple regression was significant

e. Now we have to examine both predictors to determine their significance: Number of Employees and Square Footage

â€‹i. Use t(Total) = _________ , p ________ for each predictor

Number of employees: t(13) = .04, p = .97 Ã not sig. because p is above .05

Square footage: t(13) = 9.88, p < .001 Ã sig. because p is below .05

f. The write-up must include the discussion about R2, whether or not the multiple regression test used was significant (F (df) = _________, p ______) and if the predictors were significant using t(Total) = ______ , p ______.

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