Answer:
Null hypothesis:
Alternative hypothesis:
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 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:
Alternative hypothesis:
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 assumed for the statistical test