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?

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.