Question

# A USA Today article claims that the proportion of people who believe global warming is a...

A USA Today article claims that the proportion of people who believe global warming is a serious issue is 0.59, but given the number of people you've talked to about this same issue, you believe it is greater than 0.59. The hypotheses for this test are Null Hypothesis: p ≤ 0.59, Alternative Hypothesis: p > 0.59. You take a random sample and perform a hypothesis test, getting a p-value of 0.9623. What is the appropriate conclusion? Conclude at the 5% level of significance.

Question options:

 1) The proportion of people who believe global warming is a serious issue is significantly larger than 0.59.
 2) We did not find enough evidence to say the proportion of people who believe global warming is a serious issue is less than 0.59.
 3) We did not find enough evidence to say a significant difference exists between the proportion of people who believe global warming is a serious issue and 0.59
 4) The proportion of people who believe global warming is a serious issue is less than or equal to 0.59.
 5) We did not find enough evidence to say the proportion of people who believe global warming is a serious issue is larger than 0.59.

Question (1 point)

In the year 2000, the average car had a fuel economy of 21.3 MPG. You are curious as to whether the average in the present day is greater than the historical value. The hypotheses for this scenario are as follows: Null Hypothesis: μ ≤ 21.3, Alternative Hypothesis: μ > 21.3. If the true average fuel economy today is 19.7 MPG and the null hypothesis is rejected, did a type I, type II, or no error occur?

Question options:

 1) Type II Error has occurred
 2) Type I Error has occurred.
 3) No error has occurred.
 4) We do not know the degrees of freedom, so we cannot determine if an error has occurred.
 5) We do not know the p-value, so we cannot determine if an error has occurred.

1)

p is very large

So,

 5) We did not find enough evidence to say the proportion of people who believe global warming is a serious issue is larger than 0.59.

2)

Type I and type II errors. ... In statistical hypothesis testing, a type I error is the rejection of a true null hypothesis (also known as a "false positive" finding or conclusion), while a type II error is the failure to reject a false null hypothesis (also known as a "false negative" finding or conclusion).

 2) Type I Error has occurred.

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