Analysis Of Young People’s Career By Use Of Markov Chains: Case Study Of Kisumu City

ABSTRACT

It is the desire of every person to have a career. Not much thought has been taken

by young people on how they can arrive at their future careers. The reason is mainly

because they are not aware. As much as many people have attained their careers through

education, not much consideration has been given to the other factors within education

that leads one to his or her career. The study traced one’s career from primary to present

position. There are stages one follows to reach the career, which are called states in this

study. The predicament of these young people is dealt with by use of Markov chains.

Markov chains is a process that consists of finite number of states, which are four in

this study. The four states that were considered in this study are, KCPE, KCSE, College

and Career. KCPE, KCSE and College are transient states, while career is the final state.

Regardless of where they started from, they ended up in Career with different proportions.

Transitional probabilities were used to form transitional probability matrix. The matrix

so formed was used to find Fundamental Matrix. The fundamental matrix has given the

expected number of times the process was in each transient state, that is, the means. About

16 percent of those who did KCPE, 10 percent of those who did KCSE and 99 percent

of college graduates got career. This shows that not many get into career after KCPE.

Further still fewer young people get into career after KCSE, this may be because most of

them prefer to proceed to college before career. The variances associated with transition

among KCPE, KCSE and College are 0:821685, 0:037049 and 0:0069. Their respective

standard deviations are 0:906468, 0:192481 and 0:083066. The low values indicate that

the values did not deviate much from the expected, except for KCPE. Those who don’t

intend to go to college should rather identify a career path after KCPE.