Consider the population regression of log earnings [y, where y = ln(earnings)] against two binary variables: whether a worker is married (d_1, where d_1 = 1 if the person is married) and the worker's gender (d_2, where d_2 = 1 if the person is female), and the product of the two binary variables y = beta_0 + beta_1 d_1 + beta_2 d_2 + beta_3 (d_1 times d_2) + u. the interaction term (d_1 times d_2) allows the population effect on log earnings of being married to depend on gender does not make sense since it could be zero for married males indicates the effect of being married on log earnings cannot be estimated without the presence of a continuous variable

an advantage of the standard deviation is that it increases as the dispersion of the data increases. e. the interquartile range is preferred when the data are not skewed or no have outliers. an advantage of the standard deviation is that it uses all the observations in its computation.

find the magnitude of the trig term  

csc

(

x

)

−

1

by taking the absolute value of the coefficient.

1

find the lower bound of the range.

tap for more

y

=

−

2

find the upper bound of the range.

tap for more

y

=

0

the range is  

y

≤

−

2

or  

y

≥

0

.

(

−

∞

,

−

2

]

∪

[

0

,

∞

)

{

y

|

y

≤

−

2

,

y

≥

0

}

step-by-step explanation:

$5.41

step-by-step explanation:

$20 - $14.51 = $5.49.