17.6 Use least-squares regression to fit a straight line to x 1 2 34567 8 9 y 1 1.5 2 3 4 5 8 10 13 (a) Along with the slope and intercept, compute the standard error of the estimate and the correlation coefficient. Plot the data and the straight line. Assess the fit. (b) Recompute (a), but use polynomial regression to fit a parabola to the data. Compare the results with those of (a).

ratio is 2 : 9

the answer is three

13.5 : 3

step-by-step explanation:

let's assume

number of candles set =x

price of of x candles =p(x)

we are given

a candle maker prices one set of scented candles at $10 and sells an average of 200 sets each week

so, we get point as (200,10)

he finds that when he reduces the price by $1, he then sells 50 more candle sets each week

so, we can find slope

now, we can use point slope form of line

now, we can plug values

we can use point

and find b

now, we can plug it back

and we get

now, we can find revenue

we know that

revenue = price*quantity

so, we get

divide the numbers

step-by-step explanation:

i know the point slope is y= 1/11x-46/11