A financial analyst wanted to examine the relationship between salary (in $1,000) and 4 variables: age (X1= Age), experience in the field (X2= Exper), number of degrees (X3= Degrees), and number of previous jobs in the field (X4= Prevjobs). He took a sample of 20 employees and obtained the following Microsoft Excel output:

SUMMARYOUTPUT

RegressionStatistics

Multiple R0.992

R Square0.984

Adj. R Square0.979

Std. Error2.26743

Observations20

ANOVA df SS MS F SignifF

Regression 4 4609.83164 1152.45791 224.160 0.0001

Residual 15 77.11836 5.14122

Total 19 4686.95000

Coeff StdError t Stat P-Value

Intercept -9.611198 2.77988638 -3.457 0.0035

Age 1.327695 0.11491930 11.553 0.0001

Exper -0.106705 0.14265559 -0.748 0.4660

Degrees 7.311332 0.80324187 9.102 0.0001

Prevjobs -0.504168 0.44771573 -1.126 0.2778

Note:Adj. R Square= Adjusted R Square;Std. Error= Standard Error

Referring to the information above, the analyst decided to construct a 99% confidence interval for3. Thelowerbound of the confidence interval is ________ (3 d.p.)