As a researcher, imagine that you were conducting a regression analysis and examining the relationship between the number of days a released inmate was homeless

(x)

and the fiumber of theft-related offences

(y)

. You calculate a slope

(b)

of 7.81. How would you interpret this slope coefficient?\ The slope

b

is 7.81 , meaning that for every one-unit increase in the number of days homeless

(x)

for the released inmate, the expected number of theft-related offences decreases by 7.81 (y).\ The slope

b

is 7.81 , meaning that for every one-unit increase in the number of days homeless

(x)

for the released inmate, the expected number of theft-related offences multiplies by 7.81 (

y

).\ The slope

b

is 7.81 , meaning that for every one-unit increase in the number of days homeless

(x)

for the released inmate, the expected number of theft-related offences increases by 7.81 (y).\ None of the above.

As a researcher, imagine that you were conducting a regression analysis and examining the relationship between the number of days a released inmate was homeless (x) and the fumber of theft-related offences ( y ). You calculate a slope (b) of 7.81. How would you interpret this slope coefficient? The slope b is 7.81 , meaning that for every one-unit increase in the number of days homeless (x) for the released inmate, the expected number of theft-related offences decreases by 7.81 (y). The slope b is 7.81, meaning that for every one-unit increase in the number of days homeless (x) for the released inmate, the expected number of theft-related offences multiplies by 7.81 (y). The slope b is 7.81, meaning that for every one-unit increase in the number of days homeless (x) for the released inmate, the expected number of theft-related offences increases by 7.81 (y). None of the above