Question

Tiffany Dolsing, a market analyst at the market research firm of Sanders & Sons, is analyzing household budget data collected by her firm. Tiffany’s dependent variable is monthly household expenditures on groceries (in $'s), and her independent variable is annual household income (in $1,000's). Regression analysis of the data yielded the following tables.

	Coefficients	Standard Error	t Statistic	p-value
Intercept	39.14942	22.30182	1.755436	0.109712
x	1.792312	0.407507	4.398234	0.001339

Source	df	SS	MS	F		s.e. = 29.51443
Regression	1	16850.99	16850.99	19.34446		r2 = 0.682478
Residual	9	7839.915	871.1017
Total	10	24690.91

Using α = 0.05, Tiffany should ________________.

Answer 1

Regression model is

monthly household expenditures on groceries=39.14942+1.792312*annual household income

t=4.398234

p=0.001339

alpha=0.05

p<alpha

Tiffany should reject null hypothesis and conclude that there is a linear relationship between monthly household expenditures on groceries and  annual household income.

From global F test

F=19.34446

p=F.DIST.RT(19.3446;1;9)

=0.001724757

p<0.05

Model is significant

we can use this model for predicting  monthly household expenditures on groceries based on annual household income