Answer:
A. 0.0049
B. Yes
Step-by-step explanation:
Sample proportion = 0.64
N = 1000
Population proportion = 0.60
We solve for standard deviation
= √p(1-p)/n
= √0.60(1-0.60)/1000
= √0.60x0.40/1000
= √0.00024
= 0.0155
A.
The probability of sample >=0.64
Z>=0.64-0.60/0.0155
Z >= 0.04/0.0155
So z >= 2.5806
Using excel this equal to 0.0049
0.0049 is probability of sample proportion being 0.64 at least.
B.
This answer in a shows that than 60% of households in the united states income class purchased life insurance last year.
Answer:
a. H0:μ1≥μ2
Ha:μ1<μ2
b. t=-3.076
c. Rejection region=[tcalculated<−1.717]
Reject H0
Step-by-step explanation:
a)
As the score for group 1 is lower than group 2,
Null hypothesis: H0:μ1≥μ2
Alternative hypothesis: H1:μ1<μ2
b) t test statistic for equal variances
t=(xbar1-xbar2)-(μ1-μ2)/sqrt[{1/n1+1/n2}*{((n1-1)s1²+(n2-1)s2²)/n1+n2-2}
t=63.3-70.2/sqrt[{1/11+1/13}*{((11-1)3.7²+(13-1)6.6²)/11+13-2}
t=-6.9/sqrt[{0.091+0.077}{136.9+522.72/22}]
t=-3.076
c. α=0.05, df=22
t(0.05,22)=-1.717
The rejection region is t calculated<t critical value
t<-1.717
We can see that the calculated value of t-statistic falls in rejection region and so we reject the null hypothesis at 5% significance level.
Answer:
two chop chop
Step-by-step explanation:
because it's more cheaper and money saving
1 and 1/2 is the same as 1.5 and 1.5 * 4 is 6 so I would say 4
