Which of the following statements is true about the null hypothesis?
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It is a statement that directly contradicts the null hypothesis |
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Often includes a < or > sign or states that something is not equal |
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We determine whether or not to reject this statement based on the likelihood of the opposite hypothesis being true |
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It is a statement about the population parameter |
Question 2
True or False? A small p-value indicates strong evidence against the null hypothesis
True | |
False |
Question 3
Which statement is incorrect?
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Strong evidence against the null is indicated by a p-value less than 0.05
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Weak evidence against the null is indicated by a p-value greater than 0.05
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Marginal evidence against the null is indicated by a p-value around 0.05
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All are correct |
Question 4
Which statement is NOT true?
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Type I error occurs when we measure something to be false and it is true in reality |
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No error occurs when we measure something to be significant and it is also significant in reality |
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Type II error occurs when we accept something is true in reality and measure it to be false |
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No error occurs when we accurately measure something as false |
Given Information:
Which of the following statements is true about the null hypothesis?
It is a statement that directly contradicts the null hypothesis:
False. Alternative hypothesis is a statement that directly contradicts the null hypothesis.
Often includes a < or > sign or states that something is not equal
False. Alternative hypothesis includes < or > sign or states that something is not equal ()
We determine whether or not to reject this statement based on the likelihood of the opposite hypothesis being true:
False. The null and alternative hypothesis are statements regarding the differences or effects that occur in the population. We use sample data to test which statement ( i.e., the null hypothesis or alternative hypothesis) is most likely (technically we test the evidence against the null hypothesis).
P-value is a probability of obtaining the value of the test statistic (from sample results) or more extreme, assuming the null hypothesis is true.
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