Answer:
Step-by-step explanation:
Let's put the data as below:
n1=15 x1=2.8 s1=1.6 and s1²=2.56
n2=19 x2=2.4 s2=1.7 and s2²=2.89
alpha= 0.05
To test the hypothesis:
H0= There is no sufficient evidence that low income household have fewer children
H1=There is sufficient evidence that low income household have fewer children
Assume that population variances are equal.
the t-static for two samples,
[tex]t=\frac{x1-x2}{Sp\sqrt{\frac{1}{n1}-\frac{1}{n2} \\} } }[/tex] ~t with min (n1-1,n2-1)df
The pooled variance estimate Sp equals:
[tex]Sp^{2}=\frac{(n1-1)s1^{2}+(n2-1)s2^{2} }{n1+n2-2}[/tex]
Sp²=2.7456
Sp=1.65699
Degrees of freedom=n1+n2-2=32
Under null hypothesis:
[tex]tcal=\frac{|2.8 - 2.4|}{1.6599\sqrt{\frac{1}{15}+\frac{1}{19} } }[/tex]
[tex]tcal=0.6989[/tex]
The critical value ttab=2.0369 for alpha=0.05
So we reject our null hypothesis H0
So there is sufficient evidence that low income households have fewer children than high income households