An historian of poor relief is interested in finding out what factors were most important in determining the amount of money localities in England (known as parishes) spent on aiding impoverished families in 1833, just prior to the passage of a law which overhauled the poor relief system. He randomly selects 311 parishes in England. His dependent variable is RELIEF (the amount of money the parish spent on relief per capita). Below are tables that define his independent variables and show the results of his regression procedure. Based on those results, answer questions #1 through 18:

Independent Variable	Definition
INCOME	Mean annual income of adult male farm workers in each parish
UNEMPLOYMENT	Proportion of farm laborers in each parish who were unemployed
LONDON	The distance (in miles) to London from the center of the county in which each parish was located
DENSITY	Number of people per square acre in each parish
WEALTH	Value of real estate in each parish per head of household

In addition to the numeric independent variables listed above, he also uses a number of dummy independent variables, where the value of "1" indicates that the answer to the question is "yes" and the value of "0" indicates that the answer to the question is "no":

Independent Variable	Definition
ALLOTMENT	Were farm laborers allotted a portion of their employers' land for their own use?
WORKHOUSE	Was there a workhouse in the parish?
CHILDALLOWANCE	Did the parish grant poor families allowances (extra money) if theyhad several children (usually three or more)?
SUBSIDY	Did the parish subsidize the wages of privately-employed laborers?

His research hypothesis is that INCOME, WEALTH, UNEMPLOYMENT, WORKHOUSE, LONDON, and CHILDALLOWANCE were all positively related to RELIEF, whereas DENSITY, SUBSIDY, and ALLOTMENT were negatively related to RELIEF.

For the sake of simplicity, we willtreat monetary values in equivalent U.S. dollars.

Here are the results of his regression procedure:

Dependent Variable: RELIEF

N of Cases: 311

Standard Error of Estimate: 6.548

y-intercept: 8.991

Independent Variable	Partial Regression Coefficient (b)	St. Error of b	Beta Weights (i.e., Standardized Coefficients)
INCOME	.153	.092	.094
UNEMPLOYMENT	40.626	5.343	.380
ALLOTMENT	-.859	.769	-.054
LONDON	-.03190	.010	-.180
WORKHOUSE	.288	.825	.017
CHILDALLOWANCE	4.676	1.007	.226
SUBSIDY	-.817	.955	-.040
DENSITY	-1.168	.457	-.123
WEALTH	.127	.168	.037

SourceSum of Squares

Regression 7,030.463

Residuals 12,908.653

For every $20 increase in INCOME there is, on average and controlling for the influence of the other independent variables, what increase in RELIEF?

Group of answer choices

A. an amount greater than 10

B. an amount between 0.10 and 1.0

C. an amount between 1.0 and 10

D. an amount between 0 and 0.10