A sports statistician was interested in the relationship between game attendance (in thousands) and the number of wins for baseball teams. Information was collected on several teams and was used to obtain the regression
equation ŷ = 4.9x + 15.2, where x represents the attendance (in thousands) and ŷ is the predicted number of wins.
What is the predicted number of wins for a team that has an attendance of 2,100?
25.49 wins
31.92 wins
36.82 wins
10,305.2 wins

The predicted win for 2100 attendance is 25.49. Option A is correct.

Given information:

A sports statistician was interested in the relationship between game attendance (in thousands) and the number of  wins for baseball teams.

The regression equation is

where x represents the attendance (in thousands) and ŷ is the predicted number of wins.

It is required to calculate the number of wins for an attendance of 2100 or 2.1 thousand.

The required predicted number of wins can be calculated as,

Therefore, the predicted win for 2100 attendance is 25.49.

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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,

y = number of wins

x = 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.

a4 - 3a2 - 1

step-by-step explanation:

step   1   :

equation at the end of step   1   :

  ((a4) -   3a2) -   1

step   2   :

trying to factor by splitting the middle term

2.1     factoring   a4-3a2-1  

the first term is,   a4   its coefficient is   1 .

the middle term is,   -3a2   its coefficient is   -3 .

the last term, "the constant", is   -1  

40 minutes

step-by-step explanation:

add the time and multiply by 2