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
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!
