The table shows the number of free throws a player makes in a basketball game and the number of points the player scores in the game.

Number of free throws vs. Number of Points Scored
Number of free Throws Made (f) | Numbers of Points Scored (s)
5 15
3 11
8 20
7 18
9 21

Alex used a regression calculator to find the equation of the trend line y = a x + b for the data in the table. He rounded the values for a and b on his calculator as shown below.

a = 1.7
b = 6.2

Which trend line compares the data in the table?

s = 1.7 f + 6.2
s = 6.2 f + 1.7
f = 1.7 s + 6.2
f = 6.2 s + 1.7

The regression equation of the data will be:

Step-by-step explanation:

A simple linear regression equation is used to estimate the value of the dependent variable based upon the independent variable.

The general form of a simple linear regression equation is:

Here,

y = dependent variable

x = independent variable

a = intercept

b = slope

The data is provided for the number of free throws a player makes in a basketball game and the number of points the player scores in the game.

The free throw in a basketball game implies that for every throw shot made the player receives point.

This implies that the points scored are based upon the number of free throws made by a player.

So, the dependent variable is the number of points scored and the independent variable is the number of free throws a player makes.

Then the regression equation of the data will be:

false

step-by-step explanation:

false.   two legs of the trapezoid would be congruent, but the other two would not.   were all the legs congruent, then we'd have a square; were the 2 shorter sides congruent and the 2 longer sides also congruent, we'd have a rectangle.

1/6

step-by-step explanation: