You work for a company that manages several call centers. You hire call center representatives on a regular basis and send them through a three week training program before they actually start taking calls. Unfortunately, a large percentage of the hired call center representatives don't actually make it through the program before they quit. Employees that do not make it through are called "early leavers". You are interested in being able to predict who is likely to be an "early leaver" based on information that is known during the hiring process. Therefore, you build a logistic regression model using a $0/1$ outcome $(1=$ employee was an early leaver, $0=$ employee made it through the program$).$ The results of the model are as follows:

y $=-124+\mathrm{.}03*$years of education $+\mathrm{.}22*$years of professional experience $-1\mathrm{.}28*$years of previous call center experience

Assume all of the variables are statistically significant at p$<\mathrm{.}01.$ Which of the following conclusions are supported by the model results $($check all that apply$)?$

Question $1$Select one or more:

a$.$

The more years of education an applicant has, the more likely they are to make it through the program.

b$.$

In order to decrease "early leavers", the company should target applicants with at least $5$ years of previous professional work experience.

c$.$

Every year of professional work experience increases the probability of being an "early leaver" by $\mathrm{.}22\%$

d$.$

Previous professional experience increases the likelihood that a new hire will be an "early leaver".

e$.$

In order to decrease "early leavers", the company should target applicants who have lots of previous experience in call centers.