Answer:
Type I error.
Step-by-step explanation:
Let's remember the definition of Type I error and Type II error:
A type I error is the rejection of a true null hypothesis, this means that we would get a "false positive" with this error.
A type II error is the non rejection of a not true null hypothesis, this error would give us a "false negative".
In this problem, we are told that the mean match score to identify a suspect is 80. However, the test shows that the mean match score is more than 80 when the person doesn't have a fingerprint match (and therefore the person would not be a suspect). Therefore, this person would appear as a suspect when he/she really isn't one. This means that the test is giving a "false positive". Thus, this is a type I error.
1 week is (5+2)*5. this mean in one week she spend $35 35*4 is 140.
X-intercept; -.25
y-intercept; -3
