Question

Automobile racing, high-performance driving schools, and driver education programs run by automobile clubs continue to grow in popularity. All these activities require the participant to wear a helmet that is certified by the Snell Memorial Foundation, a not-for-profit organization dedicated to research, education, testing, and development of helmet safety standards. Snell "SA" (Sports Application)-rated professional helmets are designed for auto racing and provide extreme impact resistance and high fire protection. One of the key factors in selecting a helmet is weight, since lower weight helmets tend to place less stress on the neck. The following data show the weight and price for 18 SA helmets.
W p
64 252
64 283
64 190
64 197
58 291
47 702
49 907
59 341
66 202
58 305
58 477
52 477
63 379
62 377
54 563
63 255
63 286
a. Develop a scatter diagram with weight as the independent variable.

b. Does there appear to be any relationship between these two variables?

There appears to be a - Select your answer -negativepositiveItem 2 linear relationship between the two variables. The heavier helmets tend to be less expensive.

c. Develop the estimated regression equation that could be used to predict the price given the weight.

The regression equation is (to 1 decimal and enter negative values as negative numbers). If your answer is zero enter "0".

Answer 1

Answer:

Step-by-step explanation:

Hello!

Given the variables

X₁: Weight of a safety helmet for racers

X₂: Price of a safety helmet for racers

Note, there is n= 17 observed values for each variable so for all calculations I'll use this number and disregard the 18 mentioned in the text.

a) Scatterplot in attachment.

b) If you look at the diagram it seems that there is a negative linear regression between the price and the weight of the helmets, meaning, the higher the helmet weights, the less it costs.

c) The estimated regression equation is ^Yi= a + bXi

n= 17; ∑Y= 6466; ∑Y²= 3063392; ∑X= 1008; ∑X²= 60294; ∑XY= 367536

Y[bar]= 380.35; X[bar]= 59.29

$b= \frac{sumXY-\frac{(sumX)(sumY)}{n} }{sumX^2-\frac{(sumX)^2}{n} } = \frac{367536-\frac{1008*6466}{17} }{60294-\frac{(1008)^2}{17} } = -30.18$

$a= Y[bar]- bX[bar]= 380.35-(-30.18)*59.29= 2169.77$

The estimated regression equation for the price of the helmets as a function of their weight is:

^Yi= 2169.77 -30.18Xi

I hope it helps!