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The assumption of the Law of Averages has been violated. The variables X and Y a

ID: 3375840 • Letter: T

Question

The assumption of the Law of Averages has been violated.

The variables X and Y are not related at all.

A line is an appropriate model to describe the relation between X and Y.

A line is not an appropriate model to describe the relation between X and Y.

There is not enough information about the variables X and Y to form a conclusion.

In conducting a test on the hypotheses H0: µ = 250 and Ha: µ < 250, you find that the population mean is 250 when it is actually 247. This results in what type of error?

No error

Type II error

Type I error

Standard deviation of the mean

There is not enough information given

Yes

No, the boxplot should be skewed right

No, the boxplot should be skewed left

No, the left whisker should extend to zero

No, the right whisker should extend to 45

Explanation / Answer

1. Residual plot shows the predictablity of dependent variable. if the residual plot is random and consistent around (and close to) the line then this is the ideal linear relation. if the distance increases or changes as you move from left to right or vice versa heteroscedasticity creeps in.

(Note: the image was not loaded but I can visualize the problem with the description)

2. This is Type II error.

In conducting the test you have found out that population mean is 250 i.e. you fail to reject the null hypothesis - incorrect decision. Whereas it is given that Population mean actually is 247 hence you should have been able to reject the null hypothesis. In statistical analysis whenever we fail to reject the null hypothesis when it is false is a Type II error. On the other hand whenever we reject the null hypothesis when it is actually true is also an incorrect decision with Type I error.

Note: The question has many different questions so I am just answering first two.

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