A and B are two events.
2 answers:
In order to determine if the events are independent or not we need to find the conditional probabilities.
The conditional probability of event A, given event B is denoted as P(A|B)
P(A*B) indicates P(A and B)
Using the values, we get:
Since P(A|B) is not equal to P(A) this indicates that occurrence of event B has an impact on the occurrence of event A. This shows that the two events are dependent.
Therefore, the correct option is the second one.
2. A and B are not independent events because P(A∣∣B)≠P(A)
The conditional probability of event A, given event B is denoted as P(A|B)
P(A*B) indicates P(A and B)
Using the values, we get:
Since P(A|B) is not equal to P(A) this indicates that occurrence of event B has an impact on the occurrence of event A. This shows that the two events are dependent.
Therefore, the correct option is the second one.
2. A and B are not independent events because P(A∣∣B)≠P(A)
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Answer:
a) The 99% confidence interval is from 14.8% to 23.2%.
b) The confidence interval tells us that the true proportion of mislabeled is within 14.8% and 23.2%, with a 99% confidence. In other words, if we take samples of the same size, 99% of the samples will have a proportion within 0.148 and 0.232.
c) The confidence interval calculation take into account the sample size, so the width (or precision) of the interval depends on the sample size.
The only criticism that could be analyzed is to see if the sample is representative of the population.
Step-by-step explanation:
a) We have to calculate a 99% confidence interval for the proportion.
The sample proportion is p=0.19.
The standard error of the proportion is:
The critical z-value for a 99% confidence interval is z=2.576.
The margin of error (MOE) can be calculated as:
Then, the lower and upper bounds of the confidence interval are:
The 99% confidence interval for the population proportion is (0.148, 0.232).