Answer:
P(A) = 0.2
P(B) = 0.25
P(A&B) = 0.05
P(A|B) = 0.2
P(A|B) = P(A) = 0.2
Step-by-step explanation:
P(A) is the probability that the selected student plays soccer.
Then:
P(B) is the probability that the selected student plays basketball.
Then:
P(A and B) is the probability that the selected student plays soccer and basketball:
P(A|B) is the probability that the student plays soccer given that he plays basketball. In this case, as it is given that he plays basketball only 10 out of 50 plays soccer:
P(A | B) is equal to P(A), because the proportion of students that play soccer is equal between the total group of students and within the group that plays basketball. We could assume that the probability of a student playing soccer is independent of the event that he plays basketball.
Answer:
The predicted number of wins for a team that has an attendance of 2,100 is 25.49.
Step-by-step explanation:
The regression equation for the relationship between game attendance (in thousands) and the number of wins for baseball teams is as follows:
Here,
<em>y</em> = number of wins
<em>x</em> = attendance (in thousands)
Compute the number of wins for a team that has an attendance of 2,100 as follows:
Thus, the predicted number of wins for a team that has an attendance of 2,100 is 25.49.
700 - 175 is equal to 525 when you divide that by 35 you get 15 which is your answer.
Let y represent the original price of potatoes per pound
Since he purchased the potatoes at 40% off the original price, this can represented as y*(1-0.4)
Now the weight of potatoes he purchased is x pounds, the total cost of these potatoes can be represented as x*y*(1-0.4)
The total amount of money he had is $10
The amount of money left over can be represented by the expression =
10 - x*y*(1-0.4)
where "x" is the weight of potatoes in pounds and "y" is the original price per pound of potatoes
