Suppose a gas station monitors how many bags of ice they sell along with the maximum daily temperature for 100 days. A gas station data analyst plots the data in a scatter plot with temperature, in °F, on the horizontal axis and the number of bags of ice sold on the vertical axis. She calculates a linear correlation coefficient of r = 0.9952 . The mean temperature is 84.1259 °F with a standard deviation of 9.6121 °F. The mean number of ice bags sold is 71.1173 with a standard deviation of 30.2413. Determine the slope, b , and the intercept, a , of the least-squares regression line for this dataset, precise to two decimal places.

Slope=b= 2.46

Intercept=a= -135

No. of bags sold= 78 at 87 F temperature

Complete solution with calculation is given in the pictures attached.

the value of v.w= -12.

step-by-step explanation:

we are given three vector r,v and w as:

r = < 5, -5, -2> ; v = < 2, -8, -8> ; w = < -2, 6, -5>

we know that r,v and w could also be represented as:

r=5i-5j-2k

v=2i-8j-8k

and w= -2i+6j-5k

where i,j and k are the unit vectors of x,y and z-axis respectively.

also we know that it has the following property:

i.i=1 ; j.j=1; k.k=1

and i.=j.i=i.k=k.i=j.k=k.j=0

i.e. when we multiply two vectors or we find it's dot product we need to only multiply the components of x coordinates with each other; y with each other and z with each other.

hence, v.w= (2i-8j- -2i+6j-5k)

                  = 2×(-2)+(-8)×(6)+(-8)×(-5)

                  = -4-48+40

                  = -12

hence, v.w= -12

.632

step-by-step explanation:

6 * 1/10 = 3/5

3*0.01 = 0.03

3/5 + 0.03 = .63

2*0.002 = .002

.63 + 0.002 = .632