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. A Markov chain 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.