An urban economist is curious if the distribution in where Oregon residents live is different today than it was in 1990. She observes that today there are approximately 3,109 thousand residents in NW Oregon, 902 thousand residents in SW Oregon, 244 thousand in Central Oregon, and 102 thousand in Eastern Oregon. She knows that in 1990 the breakdown was as follows: 72.7% NW Oregon, 20.7% SW Oregon, 4.8% Central Oregon, and 2.8% Eastern Oregon.

Can she conclude that the distribution in residence is different today at a 0.05 level of significance?

a) Yes, because the p-value = .0009.

b) No, because the p-value = .0009.

c) Yes, because the p-value = .0172.

d) No, because the p-value = .0172.

c) Yes, because the p-value = 0.0172

Step-by-step explanation:

The following table is obtained:

Categories       Observed(fo)        Expected (fe)        (fo-fe)²/fe

NW Oregon        3109           4357*0.727=3167.539       1.082

SW Oregon        902             4357*0.207=901.899           0

Central Oregon    244          4357*0.048=209.136         5.812

Eastern Oregon    102           4357*0.028=121.996         3.277

Sum =                    4357        4357                                   10.171

(1) Null and Alternative Hypotheses

The following null and alternative hypotheses need to be tested:

H0:p1=0.727,p2=0.207,p3=0.048,p4=0.028

Ha: Some of the population proportions differ from the values stated in the null hypothesis

This corresponds to a Chi-Square test for Goodness of Fit.

(2) Rejection Region

Based on the information provided, the significance level is α=0.05, the number of degrees of freedom is df=4−1=3, so then the rejection region for this test is R={χ2:χ2>7.815}.

(3) Test Statistics

The Chi-Squared statistic is computed as follows:

(4) Decision about the null hypothesis

Since it is observed that

it is then concluded that the null hypothesis is rejected.

(5) Conclusion

It is concluded that the null hypothesis H_o is rejected. Therefore, there is enough evidence to claim that some of the population proportions differ from those stated in the null hypothesis, at the α=0.05 significance level.

c

step-by-step explanation:

i think because what else can be a sample of every member

15% chance.

step-by-step explanation:

3/10 times, the 5 year old will get a tablet. 5/10 times, the 13 yer old will get a tablet. multiply both fractions to get 15/100 times, both would have a tablet.