A software firm collected data for a sample of 30 computer programmers. Regression analysis can be used to determine if the annual salary ($1000s) was related to the years of experience, the score on the firm’s programmer aptitude test, and gender.

Question: To determine the joint significance of the two factors, test score, and gender, in model 1, one should use

Model 1:

	Coefficients		Standard Error
Intercept		9.3536		6.2008
experience		1.4888		0.1829
Test score		0.1851		0.0757
female		-2.3613		1.0607

SST=599.7855, SSE= 75.9380

Model 2:

	Coefficients	Standard Error
Intercept	-3.3550	13.2026
test score	0.4214	0.1538
female	-0.5609	2.2824

SST=599.7855, SSE= 390.5162

Model 3:

	Coefficients	Standard Error
Intercept	24.2883	1.2394
experience	1.6603	0.1921
female	-3.3741	1.1106

SST=599.7855, SSE= 104.3472

Model 4:

	Coefficients	Standard Error
Intercept	3.1739	6.1561
experience	1.4039	0.1986
test score	0.2509	0.0774

SST=599.7855, SSE= 99.4570

Model 5:

	Coefficients	Standard Error
Intercept	22.8111		1.3761
experience	1.6200		0.2313

SST=599.7855, SSE=160.9988

Model 6:

	Coefficients	Standard Error
Intercept	-4.7097	11.6794
test score	0.4344	0.1406

SST=599.7855, SSE=391.9035

Model 7:

	Coefficients	Standard Error
Intercept	32.59		1.7687
female	-2.71		2.5013

SST=599.7855, SSE=563.065

options:

	t-test or F test
	partial F test
	t-test
	overall F test