Question

his situation is the same for questions 2 - 6. A few years​ ago, a census bureau reported that​ 67.4% of American families owned their homes. Census data reveal that the ownership rate in one small city is much lower. The city council is debating a plan to offer tax breaks to​ first-time home buyers in order to encourage people to become homeowners. They decide to adopt the plan on a​ 2-year trial basis and use the data they collect to make a decision about continuing the tax breaks. Since this plan costs the city tax​ revenues, they will continue to use it only if there is strong evidence that the rate of home ownership is increasing. What would a Type I error be?

Answer 1

Answer:

Type 1 Error: Stating 'American families owing house< 67.4%', when it = 67.4%

And, implementing the tax break for first time home buyers, due to the error

Step-by-step explanation:

Null Hypothesis [H0] : American families owing house = 67.4%

Alternate Hypothesis [H1] : American families owing house < 67.4%

Type 1 error is he rejection of an actually true null hypothesis.

In this case, it means : Results reject H0 in favour of H1 & state that 'american families owing house < 67.4% ; when actually null hypothesis, i.e 'american families owing house = 67.4%'  is true.

This would imply that city council might extend the tax breaks for first time home buyers because of the type 1 error in the case. When, it is actually not needed as per the true data status.