Time Series Analysis On The Total Number Of Patients Treated For Malaria Fever

Time Series Analysis On The Total Number Of Patients Treated For Malaria Fever


This project work revealed the rate at which people are infected with malaria the least square method used for analysis showed that people are infected with malaria irrespective of the time and seasons of a successive year, There is no noticeable direction as regarding the number of patient treated for malaria over time.

Also, the analysis from autoregressive moving average report shows that both autoregressive and moving average of order four were both appropriate while the report from autocorrelation and autocovariance does not indicate any noticeable trend in the number of patients treated for malaria.



The term time series refers to one the quantitative method used in determination pattern in data collected over time e.g weekly monthly, quarterly or yearly.

Time service is the statistic tool or methodology that can be used to transform past experience to predict future event which would enable the researcher or organization to plan.

It gives information about how the particular case of study has been behaving in the past and present and such information can be used in prediction The number of people treated for malaria fever at the otan Ayegbaju management hospital. Comprehensive health centre otan. We are going to seen how change occur over mouths in each year in the occurrence of the disease in the hospital. As a result of this, we will be able to know certain factor responsible for increase or decrease in the rate of infection of the disease over the period of time.

Record of time series data can be made in the following ways:-


This can be referred to the general path in which time series graph appear to follow over a long period of time, in other word, it is the long-term increase or decrease in a variable being measured over time for example a company planning her expense on goods to produce in the next three or four years has consider demand at a particular time.



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