The statement that 99% of all confidence intervals with a 99% confidence level should contain the population parameter of interest is false.
A confidence interval (CI) is essentially a range of estimates for an unknown parameter in frequentist statistics. The most frequent confidence level is 95%, but other levels, such 90% or 99%, are infrequently used for generating confidence intervals.
The confidence level is a measurement of the proportion of long-term associated CIs that include the parameter's true value. This is closely related to the moment-based estimate approach.
In a straightforward illustration, when the population mean is the quantity that needs to be estimated, the sample mean is a straightforward estimate. The population variance can also be calculated using the sample variance. Using the sample mean and the true mean's probability.
Hence we can generally infer that the given statement is false.
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Sample space ={5G, 2Y, 8R, 3P} =18 POSSIBLE OUTCOME
1st draw: P(R) = 8/18 = 4/9 = 0.444
2nd draw (no replacement, means already one Red is picked up, so the sample space has been reduced): P(another one more RED) = 7/17 =0.411
First, the difference is 7/2 - 6/4 = 14/4 - 6/4 = 8/4
Now multiply it: 8/4 x (-2/5) = -16/20 = -4/5
Answer:
B. a6b8c3
Step-by-step explanation:
