Answer:
15.87% of the total number of cardholder would be expected to be charging 27 or more in the study.
Step-by-step explanation:
Normal Probability Distribution:
Problems of normal distributions can be solved using the z-score formula.
In a set with mean
and standard deviation
, the z-score of a measure X is given by:

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.
Mean of 25 charged purchases and a standard distribution of 2
This means that 
Proportion above 27
1 subtracted by the pvalue of Z when X = 27. So



has a pvalue of 0.8413
1 - 0.8413 = 0.1587
Out of the total number of cardholders about how many would you expect are charging 27 or more in the study?
0.1587*100% = 15.87%
15.87% of the total number of cardholder would be expected to be charging 27 or more in the study.
If your answer was d) 3.6 , then you are correct!
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.