1. In conducting a test on the hypotheses H0: µ = 250 and Ha: µ < 250, you find
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Question
1. 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
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.
Explanation / Answer
1. In this case H0: µ = 250
Ha: µ < 250
The null hypothesis is not rejected when it is false, this is called as type II error.
Same situation happens here that you find the population mean is 250 that means null hypothesis is not rejected when it is actually 247 that alternative hypothesis is true.
So this results is type II error.
2. Sum of residuals is zero. That means the points scattered above and below the x axis in such a way that the distance from the x axis should be constant (not to increases or decrease).
A residual plots is shown with 18 points scattered above and below the x axis in such a way that the distance from the x axis increases as you move from the left.
In the above situation the constant variance assumption of residual is violated. Because the variance of the residuals is increasing with x. So this linear model is not good fit to the data.
Correct answer is A line is not an appropriate model to describe the relation between X and Y.
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