MINITAB reports the results below for the multiple regression of y = crime
rate on x1 = median income (in thousands of dollars) and x2 = urbanization.

Results of regression analysis
Predictor Coef SE Coef T P
Constant 39. 97 16. 35 2 .44 0.017
income −0.7906 0.8049 −0.98 0.330
urbanization 0.6418 0.1110 5.78 0.000

Correlations: crime, income, urbanization

crime urbanization
urbanization 0.677
income 0.434 0.731

(A) Report the prediction equations relating crime rate to income at urbanization levels of (i) 0 and (ii) 100. Interpret
(B) For the bivariate model relating y = crime rate to x =income, MINITAB reports:
crime = -11.6 + 2.61 income
Interpret the effect of income, according to the sign of its slope.

a) As income increases, the predicted amount of crime increases.
b) As income increases, the predicted amount of crime decreases.

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step-by-step explanation:

answer: 10 meter

step-by-step explanation:

need details

the largest number of the four options is 1.8 x 10-2

you have it in scientific notation.

1.80 x 10-6   = 0.00000180

1.80 x 10-4   = 0.000180 (bigger, or "less small", than the former one)

so

1.8 x 10-2       = 0.0180. as you see. the "less small", or the biggest one of them all.

as you have negative exponent, it means you are dividing 1.8 by 100 (i.e. moving the dot towards left, two times).

if you had positive exponent for the scientific notation, power of tenths, you would be multiplying times 100 (moving the dot towards right) as below:

1.8 x (10)2 = 180

so. if you have negative exponent in scientific notation, move the dot toward left. if it is positive, toward right as many times the exponent tells you.