Hello,
g=9.81m/s²= 9.81/0.3048 =32.18.. ft/s² rounded to 32
h=-g/2*t²+vt+h0
if t=0,h=0 ==>h0=0
==>h=-16*t²+vt
50 ft in 2.5s ==> 25 ft in 1.25s
25=-16*1.25²+v*1.25
==>v=50/1.25=40
Equation h=-16t²+40*t
6 + 2 < 9 + 3...u r correct
For this case, the parent function is given by:

We apply the following transformations:
Vertical translations:
Suppose that k> 0
To graph y = f (x) + k, move the graph of k units upwards:
For k = 9 we have:

Horizontal translations:
Suppose that h> 0
To graph y = f (x-h), move the graph of h units to the right
For h = 4 we have:

Answer:
The function g (x) is given by:

Correct question
Sale Price :160 | 180 | 200 | 220 | 240 | 260 | 280
New home : 126 | 103 | 82 | 75 | 82 | 40 | 20
A.) state the linear regression function that estimates the number of new homes available at a specific price.
B.) state the correlation Coefficient of the data, and explain what it means in the context of the problem
Answer:
Y = -0.79X + 249.86
R = -0.9543
Step-by-step explanation:
Sale Price :160 | 180 | 200 | 220 | 240 | 260 | 280
New home : 126 | 103 | 82 | 75 | 82 | 40 | 20
Calculate the Linear regression equation :
Using the linear regression calculator :
The linear regression equation is :
Y = -0.79X + 249.86
The correlation Coefficient 'R' measures the strength of statistical relationship between the relative movement of two variables. The The value of R is -0.9543 in the question above.
This is a strong negative correlation, which means that high sales price of homes scores correlates with low number of new homes scores (and vice versa). Homes with high sales price have fewer number of new homes.