In 2014, the size of a midwest city's population was growing at a rate of 0.673% yearly. if there were 307,000 people living in that city in 2014, find how many people (rounded to the nearest whole) should be expected in the year 2036? use p = p 0 e 0.00673 t p=p0e0.00673t, where t t is the number of years since 2014 and p 0 p0 is the initial population.

The expected number of people in 2036 is 355992

Step-by-step explanation:

The formula or equation for determining the the population of Midwest city after t years is expressed as

P = Poe0.00673t

Where

Po is the initial population

0.673% represents the rate at which the population increased yearly.

From the information given,

The total number of people that lived in Midwest city in 2014 was 307,000 people. It means that Po = 307000. The number of years between 2014 and 2036 is 22 years so t = 22. Therefore,

P = Poe0.00673 ^ 22 = 355992

a. If the P-value is smaller than the significance level, the null hypothesis is rejected.

b. Pooled proportion = 0.8

c. z = 2.7

d. As the P-value (0.0072) is smaller than the significance level (0.05), the null hypothesis is rejected.

There is enough evidence to support the claim that the proportions differ significantly.

Step-by-step explanation:

This is a hypothesis test for the difference between proportions.

We will use the P-value approach, so the decision rule is that if the P-value is lower than the significance level, the null hypothesis is rejected.

The claim is that the proportions differ significantly.

Then, the null and alternative hypothesis are:

The significance level is 0.05.

The sample 1, of size n1=200 has a proportion of p1=0.85.

The sample 2, of size n2=150 has a proportion of p2=0.7333.

The difference between proportions is (p1-p2)=0.1167.

The pooled proportion, needed to calculate the standard error, is:

The estimated standard error of the difference between means is computed using the formula:

Then, we can calculate the z-statistic as:

This test is a two-tailed test, so the P-value for this test is calculated as (using a z-table):

As the P-value (0.0072) is smaller than the significance level (0.05), the effect is significant.

The null hypothesis is rejected.

There is enough evidence to support the claim that the proportions differ significantly.