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Question
- approximately 3.5 percent of all children born in a certain region are from multiple births (twins, triplets, etc.). of the children born in the region who are from multiple births, 22 percent are left - handed. of the children born in the region who are from single births, 11 percent are left - handed.
a. draw a tree diagram to model this scenario.
b. what is the probability that a randomly selected child born in the region is left - handed? show your work.
c. what is the probability that a randomly selected child born in the region is a child from a multiple birth, given that the child selected is left - handed? show your work.
Part A: Tree Diagram Explanation
To draw the tree diagram, we start with the first level representing the type of birth (multiple or single). The probability of multiple births (\(M\)) is \(0.035\), so the probability of single births (\(S\)) is \(1 - 0.035 = 0.965\). From each of these branches, we add a second level for being left - handed (\(L\)) or right - handed (not \(L\)). For multiple births, \(P(L|M)=0.22\) and \(P(\text{not }L|M)=1 - 0.22 = 0.78\). For single births, \(P(L|S)=0.11\) and \(P(\text{not }L|S)=1 - 0.11 = 0.89\).
Part B: Probability of being left - handed
We use the law of total probability. The law of total probability states that if we have a partition of the sample space (here, the partition is multiple births \(M\) and single births \(S\)), then \(P(L)=P(L|M)P(M)+P(L|S)P(S)\)
Step 1: Identify the probabilities
We know that \(P(M) = 0.035\), \(P(L|M)=0.22\), \(P(S)=0.965\), and \(P(L|S)=0.11\)
Step 2: Apply the law of total probability
Part C: Probability of multiple births given left - handed
We use Bayes' theorem. Bayes' theorem states that \(P(M|L)=\frac{P(L|M)P(M)}{P(L)}\)
Step 1: Identify the values
We already found that \(P(L|M) = 0.22\), \(P(M)=0.035\), and \(P(L)=0.11385\) from part B.
Step 2: Apply Bayes' theorem
Part B Answer
The probability that a randomly selected child is left - handed is \(0.11385\)
Part C Answer
The probability that a randomly selected left - handed child is from a multiple birth is approximately \(0.0676\)
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Part A: Tree Diagram Explanation
To draw the tree diagram, we start with the first level representing the type of birth (multiple or single). The probability of multiple births (\(M\)) is \(0.035\), so the probability of single births (\(S\)) is \(1 - 0.035 = 0.965\). From each of these branches, we add a second level for being left - handed (\(L\)) or right - handed (not \(L\)). For multiple births, \(P(L|M)=0.22\) and \(P(\text{not }L|M)=1 - 0.22 = 0.78\). For single births, \(P(L|S)=0.11\) and \(P(\text{not }L|S)=1 - 0.11 = 0.89\).
Part B: Probability of being left - handed
We use the law of total probability. The law of total probability states that if we have a partition of the sample space (here, the partition is multiple births \(M\) and single births \(S\)), then \(P(L)=P(L|M)P(M)+P(L|S)P(S)\)
Step 1: Identify the probabilities
We know that \(P(M) = 0.035\), \(P(L|M)=0.22\), \(P(S)=0.965\), and \(P(L|S)=0.11\)
Step 2: Apply the law of total probability
Part C: Probability of multiple births given left - handed
We use Bayes' theorem. Bayes' theorem states that \(P(M|L)=\frac{P(L|M)P(M)}{P(L)}\)
Step 1: Identify the values
We already found that \(P(L|M) = 0.22\), \(P(M)=0.035\), and \(P(L)=0.11385\) from part B.
Step 2: Apply Bayes' theorem
Part B Answer
The probability that a randomly selected child is left - handed is \(0.11385\)
Part C Answer
The probability that a randomly selected left - handed child is from a multiple birth is approximately \(0.0676\)