A fast-food franchise is considering building a restaurant at a busy intersection. A financial advisor determines that the site is acceptable only if, on average, more than 300 automobiles pass the location per hour. The advisor tests the following hypotheses: H 0: μ ≤ 300. HA: μ > 300. The consequences of committing a Type I error would be that ________.

When we talk about a type I of error we are refering to a“false positive” and is associated when we reject a null hypothesis when it is actually true.

And for this special case would be reject the null hypothesis that the true mean is lower or equal than 300 [/tex]\mu\leq 300[/tex] but that in fact is true.

This type of error is associated to the significance level [tex]\alpha[/tex] assumed for the statistical test

Step-by-step explanation:

For this case we define the random variable X as the number of automobiles pass at a location per hour and we are tryng to proof this:

Null hypothesis: [tex]\mu \leq 300[/tex]

Alternative hypothesis: [tex]\mu >300[/tex]

When we talk about a type I of error we are refering to a“false positive” and is associated when we reject a null hypothesis when it is actually true.

And for this special case would be reject the null hypothesis that the true mean is lower or equal than 300 [/tex]\mu\leq 300[/tex] but that in fact is true.

This type of error is associated to the significance level [tex]\alpha[/tex] assumed for the statistical test