Time series analysis is a statistical methodology appropriate for longitudinal research designs and the data obtained is also known as longitudinal data. The data is identified and treated as a stretch/series of values and time being treated as the parameter . The process of data collection follows time as a parameter. Time series analysis has some important advantages over other methodologies in that it provides the opportunity to investigate the pattern of intervention effects across time. Velicer, 2003, has identified five pointers to be followed when such a longitudinal framework is applied, a) Are the effects of intervention temporary or permanent; b) Does the intervention cause a change in the ‘slope’ of the behavior process as well as the overall level; c) Does the intervention cause a change in any cycling that is present in the underlying behavior process; d) Does the intervention cause the variance to change; e) Does the intervention cause a change in the nature of the dependency that is present in the time series process.