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Here is an intuitive explanation (i do not want to get into probabilistic formalism): When you calculate the confidence interval you “hope” to “catch” the true value of the parameter inside the interval. Higher confidence level means that it is “easier” to catch it. The 96. 6% confidence interval for is a.
60. 76 to 69. 24 c. 61. 08 to 68. 92 d. 60. 00 to 80. 00 ans: The average length of time it took these 100 customers to check out was 3. 0 minutes. . 0001pt”>question 1an investigator claims, with 95 percent confidence, that the interval between 10 and 16 miles includes the mean commute distance for. The higher the confidence level, the wider the confidence interval. This should make sense intuitively: A wider confidence level has a higher probability of containing a true population parameter. A confidence interval is a range of values that is likely to contain a population parameter with a certain level of confidence.
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