Which one of the following statements is the correct interpretation of P-value ofless than 0.01 in hypothesis testing?
A. There is overwhelming evidence to infer that the alternative hypothesis is true
B. There is strong evidence to infer that the alternative hypothesis is true
C. There is weak evidence to indicate that the alternative hypothesis is true
D. There is no evidence to infer that the alternative hypothesis is true
Answer: Option A
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A. The central limit theorem
B. The law of statistical regularly
C. The law of inertia of large numbers
D. None of the above
The difference between sample statistic and its corresponding population parameter is
A. Sampling error
B. Measurement error
C. Coverage error
D. Non-response error
A. Both (A) and (R) are true
B. (A) is true, but (R) is false
C. (A) is false, but (R) is true
D. Both (A) and (R) are false
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