To study about the relationship between height and the weight, you need to collect a sample of nine (9) people using a systematic sampling method.
What is the population of people?
Where and how are you going to collect your sample?
Does your sample accurately represent your population? Why or why not?
Collect the sample and record the data.
(CLO 1) Construct a confidence interval to estimate the mean height and the mean weight by completing the following:
Find the sample mean and the sample standard deviation of the height.
Find the sample mean and the sample standard deviation of the weight.
Construct and interpret a confidence interval to estimate the mean height.
Construct and interpret a confidence interval to estimate the mean weight.
(CLO 2) Test a claim that the mean height of people you know is not equal to 64 inches using the p-value method or the traditional method by completing the following:
State H0 and H1.
Find the p value or critical value(s).
Draw a conclusion in context of the situation.
(CLO 3) Create a scatterplot with the height on the x-axis and the weight on the y-axis. Find the correlation coefficient between the height and the weight. What does the correlation coefficient tell you about your data? Construct the equation of the regression line and use it to predict the weight of a person who is 68 inches tall.
Write a paragraph or two about what you have learned from this process. When you read, see, or hear a statistic in the future, what skills will you apply to know whether you can trust the result?
. But there is no guarantee that the images and identities are safe. The data can be misused and when the data is shared, the individual’s privacy is gone. The misuse of the technology is one ethical aspect that needs to be concerned. The technology may gain unintended purposes. There have been numerous incidents in which video cameras were focused on inappropriate areas, for example on bedroom windows. Once it is determined that an individual’s face does not match with the database, the facial signature is supposed to be deleted. But there is no evidence that the identities are deleted. They can also be stockpiled, so they can be used in the future and can be shared among for instance other governmental agencies . iii. Problem of error The last ethical aspect to consider is the problem of error, which is the fact that incorrect matches can be made with face recognition technologies. This can lead to accusing innocent citizens. This is not always the fault of the technologies, but can occur in any database system with personal data. It would be acceptable to use facial recognition if a good ratio can be attained between false and true positive results. Provided that the individuals who are rated as a false positive are treated well and they are not questioned in an improper way. People have accepted that they sometimes have to endure minor inconveniences to be able to detect criminals. But in case there are too many false positives for each true positive, the harm done to innocent people is more important than detecting or arresting a criminal . The systems should be tested on their performance before they are used. With the information this provides, improvements can be made to the systems in order to reduce the rate of false positives . The challenge is how to trade-off between privacy and the security of facial recognition systems. One cannot prevaricate the loss of privacy by using facial recognition in everyday life. But the question is, is the improvement in security enough relative to the loss of the individual’s privacy? There is not one specific answer to this question. There are and there always will be proponents and oppon>GET ANSWER