5. (02.05 LC)
Prior to fitting a linear regression model with x and y variables, both variables were transformed using logarithms. The following computer output was produced.

Coefficients Standard Error t Stat P-value
Intercept 5.672 1.483 22.98 0.0002
Log (x) −2.583 0.037 −7.56 0.0003

R-sq. = 82.14% R-sq.(adj) = 81.25%

Part A: Interpret the value of r2. (5 points)
Part B: Assuming the residual plot of the transformed data shows a pattern, comment on the appropriateness of this linear regression for modeling the relationship between the transformed variables. (5 points)

answer:

ok sir

explanation:

answer:

b 2 +3

explanation:

cause

answer:

2

explanation:

1+1 = 2

the reason this is so is because of basic addition. we can double check this without using addition if you really want. if you take 1+1=x, subtract 1 from both sides than you get 1 = x - 1. subtract x from both sides and you get 1 - x = -1. subtract 1 from both sides again and you get -x = -2. finally, multiply both sides by -1 to get x = 2. subtraction is still technically addition you say? fine, have it your way. 1 + 1 = x. by definition, adding something to itself is the same thing as multiplying it by 2. this means we can technically rewrite the equation as

1 * 2 = x. now all we have to do is solve it. 1 * 2 = x when simplified results in 2 = x, or x = 2. this shows 1 + 1 = x. you say you want a real answer. you want me to start you from the ground up? well i would, but that would practically just be stealing from what was written on this website: go check it out if you really need to.