CHAPTER ONE
1.0   INTRODUCTION
The need to monitor, evaluate and make adequate plans for the future compels managers, scientist of various calling and researchers alike to collect data on regular basis on processes that vary as time passes. Observations on such processes when arranged in chronological order (in time sequence) are called time series. A time series is a group of data that has been collected successively over a period of time. Some examples of time series are: the daily cash-deposits of customers, the weekly recorded cash-deposits of the bank, and the weekly or monthly stock levels of a company, the number of patients treated by a particular hospital per annum.
The method of analyzing and interpreting these data is referred to as time series analysis. Time series analysis is very important in business and economic for forecasting purposes.
As we tend to base our forecast of cash-deposit results on what has happened in the past. The statistical series which tells us how data has been behaving in the past is the time series. It gives us the values of variable we are considering at various points in time each year for the last ten years. Time series may be classified as follows:
SECULAR TREND: This is refers to the general direction in which the figures appears to the going over a long interval of time. It is important to distinguish between trends resulting from cyclical influence on the economy. Example, a change in task of customers buying habits. The observation of a secular trend might show an upward trend or downward trend or a steady trend.
SEASONAL VARIATIONS: It is a common knowledge and a clear view to all that the value of many variables depends partly on the time of the year in question, every one knows that the rate of cash-deposits of customers is usually high in the month of March to November, during which customers stock their cash in banks, that is in order of months.
CYCLICAL VARIATION: As the economy expands during the period of boom, we would expect to find that such data like cash-deposits, cash withdrawals or customers expenditure and sells rate will show a rising trend, and during the period of slump, we would expect them to show downward trend. Thus a wave-like motion may be observed in the pattern of our data.
IRREGULAR VARIATION: These are random external events which affects our variables. May are also referred to as random variations because they result from sporadic events such as strikes, earth-quakes, floods, fire disaster, riots and this events are unpredictable.
It is very clear that time series analysis will help in finding the trend to guide this industry or sector in forecasting and other management decisions that pertain to competition. In order to create a conducive condition or climate favourable for business, sponsoring the national football league and all national volley ball league or basket ball league is just a few. Their management slogan is “We keep our word”.