Answer:
The probability that our guess is correct = 0.857.
Step-by-step explanation:
The given question is based on A Conditional Probability with Biased Coins.
Given data:
P(Head | A) = 0.1
P(Head | B) = 0.6
<u>By using Bayes' theorem:</u>
We know that P(B) = 0.5 = P(A), because coins A and B are equally likely to be picked.
Now,
P(Head) = P(A) × P(head | A) + P(B) × P(Head | B)
By putting the value, we get
P(Head) = 0.5 × 0.1 + 0.5 × 0.6
P(Head) = 0.35
Now put this value in , we get
Similarly.
Hence, the probability that our guess is correct = 0.857.
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Answer: D. To produce treatment groups with similar characteristics
Step-by-step explanation:
By using randomization in sampling, the Sample would be more representative of the Population it is based off of because different demographic characteristics may be picked.
This leads to a situation where the groups have similar characteristics between themselves thereby making it easier for comparison. For example, Group 1 would have certain types of people that will be represented in Group 2 and Group 3 as well. That way the effects of the drug can be properly studied as it affects different people. For instance, say there are 4 obese people in a sample of 10, instead of group one having all obese people, randomization may be able to give group one, 2 obese people and 2 obese people to group 2 as well. That way when comparing, the effects of the drug on the two groups is easier to be compared because the two groups have similar people.
Answer:
1250 pounds
Step-by-step explanation:
1625=x+30%
1625=1.3x
x=1250
