The events A and B are independent if the probability that event A occurs does not affect the probability that event B occurs.
A and B are independent if the equation P(A∩B) = P(A) P(B) holds true.
P(A∩B) is the probability that both event A and B occur.
Conditional probability is the probability of an event given that some other event first occurs.
P(B|A)=P(A∩B)/P(A)
In the case where events<span> A and B are </span>independent<span> the </span>conditional probability<span> of </span>event<span> B given </span>event<span> A is simply the </span>probability<span> of </span>event<span> B, that is P(B).</span>
Statement 1:A and B are independent events because P(A∣B) = P(A) = 0.12. This is true.
Statement 2:<span>A and B are independent events because P(A∣B) = P(A) = 0.25.
This is true.
Statement 3:</span><span>A and B are not independent events because P(A∣B) = 0.12 and P(A) = 0.25.
This is true.
Statement 4:</span><span>A and B are not independent events because P(A∣B) = 0.375 and P(A) = 0.25
This is true.</span>
Equals the third side length
Answer:
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Answer:number of juice and fruits
Step-by-step explanation:
juice and fruits
In statistical methods, the significance level is a value that is used as a criterion for rejecting a null hypothesis. It used by first looking at the differences between the experimental results and from there the null hypothesis would be determined. Then, we assume that the null hypothesis is true, the probability of the differences is computed by using statistical tools. If the computed probability is less than or equal to the value of the significance level, then you conclude that the null hypothesis should be rejected and that the results are statistically significant. Usually, a significance level of 1% or 5% is used.
